diff --git a/pydata-new-york-city-2023/category.json b/pydata-new-york-city-2023/category.json new file mode 100644 index 000000000..1cfb48fd3 --- /dev/null +++ b/pydata-new-york-city-2023/category.json @@ -0,0 +1,3 @@ +{ + "title": "PyData New York City 2023" +} diff --git a/pydata-new-york-city-2023/videos/aaditya-bhat-self-service-analytics-using-llms-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/aaditya-bhat-self-service-analytics-using-llms-pydata-nyc-2023.json new file mode 100644 index 000000000..b4486bf25 --- /dev/null +++ b/pydata-new-york-city-2023/videos/aaditya-bhat-self-service-analytics-using-llms-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://docs.google.com/presentation/d/1Oo_b1AoPASOLV6nyM8TWOvvBEKbxTPyG/edit?usp=drive_link\n\nExplore the intricacies of designing, implementing, and maintaining a production-ready LLM-based self-serve analytics platform. Learn about common pitfalls, essential design considerations, performance evaluation, and robust security measures like protection against prompt injection attacks.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2338, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://docs.google.com/presentation/d/1Oo_b1AoPASOLV6nyM8TWOvvBEKbxTPyG/edit?usp=drive_link", + "url": "https://docs.google.com/presentation/d/1Oo_b1AoPASOLV6nyM8TWOvvBEKbxTPyG/edit?usp=drive_link" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/hiYHBjmF2Eg/maxresdefault.jpg", + "title": "Aaditya Bhat - Self-Service Analytics using LLMs | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=hiYHBjmF2Eg" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/aleksander-molak-a-practical-guide-to-causality-in-python-for-the-perplexed-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/aleksander-molak-a-practical-guide-to-causality-in-python-for-the-perplexed-pydata-nyc-2023.json new file mode 100644 index 000000000..b1162fd77 --- /dev/null +++ b/pydata-new-york-city-2023/videos/aleksander-molak-a-practical-guide-to-causality-in-python-for-the-perplexed-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nWith an average of 3.2 new papers published on Arxiv every day in 2022, causal inference has exploded in popularity, attracting large amount of talent and interest from top researchers and institutions including industry giants like Amazon or Microsoft.\n\nThere\u2019s a very good reason for this upsurge in popularity. In our contemporary data culture we got accustomed to thinking that traditional machine learning methods can provide us with answers to any interesting business or scientific questions.\n\nThis view turns out to be incorrect. Many interesting business and scientific questions are causal in their nature and traditional machine learning methods are not suitable to address them.\n\nIn this talk, dedicated to data scientists and machine learning engineers with at least 3 years of experience, we\u2019ll show why this is the case, we\u2019ll introduce the fundamental tools for causal thinking and show how to translate them into code.\n\nWe\u2019ll discuss a popular use case of churn prevention and demonstrate why only causal models should be used to solve it.\n\nAll in Python, repo included!\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2559, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/e2Q6r6I4QVA/maxresdefault.jpg", + "title": "Aleksander Molak - A Practical Guide to Causality in Python (For The Perplexed) | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=e2Q6r6I4QVA" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/alexander-cs-hendorf-ten-years-of-community-organizer-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/alexander-cs-hendorf-ten-years-of-community-organizer-pydata-nyc-2023.json new file mode 100644 index 000000000..6cacd34b0 --- /dev/null +++ b/pydata-new-york-city-2023/videos/alexander-cs-hendorf-ten-years-of-community-organizer-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1BFiYjap4t92GR_FtAhHOaK5X_WeiANwX/view?usp=drive_link\n\nAs a community organizer, I have had the privilege of being a part of the Python community for the past ten years.\n\nIn that time, I have seen the community grow and evolve in countless ways. Python evolved from a top 10 language to the top 1 language. Many new people joined the community, new topics as data & AI became part of Python. I'm super proud the preferred language to learn is Python nowadays.\n\nI have also learned a great deal about what it takes to be an effective organizer and how to build and sustain a healthy community. I also experience how not to do it and pulling through in hard times.\n\nI learned a lot about leadership. I learned a lot about myself, my strength and my weaknesses.\nThis helped me also to grow professionally and had a very positive impact on how I work and lead in my day-job as partner in a data and AI consultancy.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2561, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://drive.google.com/file/d/1BFiYjap4t92GR_FtAhHOaK5X_WeiANwX/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1BFiYjap4t92GR_FtAhHOaK5X_WeiANwX/view?usp=drive_link" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/NcO2v6DDH10/maxresdefault.webp", + "title": "Alexander CS Hendorf - Ten Years of Community Organizer | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=NcO2v6DDH10" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/andy-fundinger-adventures-in-not-writing-tests-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/andy-fundinger-adventures-in-not-writing-tests-pydata-nyc-2023.json new file mode 100644 index 000000000..d5713bbec --- /dev/null +++ b/pydata-new-york-city-2023/videos/andy-fundinger-adventures-in-not-writing-tests-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1FZ6GgWplGe8j_fKmfqAKNmYmTHQgrEd2/view?usp=drive_link\n\nDeveloping reliable code without writing tests may be a far off dream, but Hypothesis' ghostwriter function will generate tests from type hints. The resulting tests are powerful and often appropriate for data analysis. In this talk, I'll discuss how to add tests to your data analysis code that cover a wide range of inputs -- all while using just a small amount of code.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1840, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://drive.google.com/file/d/1FZ6GgWplGe8j_fKmfqAKNmYmTHQgrEd2/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1FZ6GgWplGe8j_fKmfqAKNmYmTHQgrEd2/view?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/4WpJPn0_qXY/maxresdefault.jpg", + "title": "Andy Fundinger - Adventures in not writing tests | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=4WpJPn0_qXY" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/andy-terrel-the-beauty-and-the-beast-python-on-gpus-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/andy-terrel-the-beauty-and-the-beast-python-on-gpus-pydata-nyc-2023.json new file mode 100644 index 000000000..af4e83db4 --- /dev/null +++ b/pydata-new-york-city-2023/videos/andy-terrel-the-beauty-and-the-beast-python-on-gpus-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nPython promises productivity, GPUs promise performance, but if you ever try to fire up a program on a GPU you will find that it is often slower than a CPU. Over the last decade, the Python ecosystem has embraced GPUs in numerous libraries and techniques. We survey what works with GPUs and some of the libraries that one can use to accelerate the Python workflow on a GPU.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2182, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/_URmd_ff8HU/maxresdefault.jpg", + "title": "Andy Terrel - The Beauty and the Beast: Python on GPUS | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=_URmd_ff8HU" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/avishek-panigrahi-bad-data-anecdotes-and-examples-from-the-real-world-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/avishek-panigrahi-bad-data-anecdotes-and-examples-from-the-real-world-pydata-nyc-2023.json new file mode 100644 index 000000000..5c081afd1 --- /dev/null +++ b/pydata-new-york-city-2023/videos/avishek-panigrahi-bad-data-anecdotes-and-examples-from-the-real-world-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1kNBoM5txEUvrx4oaJpuX4vHGBdAh9xPU/view?usp=drive_link\n\nMany data science initiatives fail because of the unavailability of good data.\n\nIn this talk, I go over examples of bad data I\u2019ve encountered in real life projects. I present hypotheses about the reasons that lead to bad data; tools, techniques and patterns to \u201cdebug and correct\u201d bad data; simple workflows for validation, verification and automation to identify bad data using commonly available tools from the PyData and Python ecosystem. Finally, I\u2019ll go over some prescriptive techniques for how you can approach data projects with non-ideal-data to improve odds of success.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2126, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://drive.google.com/file/d/1kNBoM5txEUvrx4oaJpuX4vHGBdAh9xPU/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1kNBoM5txEUvrx4oaJpuX4vHGBdAh9xPU/view?usp=drive_link" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/LZU5fO1cE5g/maxresdefault.jpg", + "title": "Avishek Panigrahi - Bad data - anecdotes and examples from the real world | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=LZU5fO1cE5g" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/blackwood-vidos-creating-interactive-animated-reports-in-streamlit-with-vizzu-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/blackwood-vidos-creating-interactive-animated-reports-in-streamlit-with-vizzu-pydata-nyc-2023.json new file mode 100644 index 000000000..b1667dfc2 --- /dev/null +++ b/pydata-new-york-city-2023/videos/blackwood-vidos-creating-interactive-animated-reports-in-streamlit-with-vizzu-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nData scientists strive to bridge the gap between raw data and actionable insights. Yet, the actual value of data lies in its accessibility to non-data experts who can unlock its potential independently. Join us in this hands-on tutorial hosted by experts from Vizzu and Streamlit to discover how to transform data analysis into a dynamic, interactive experience.\n\nStreamlit, celebrated for its user-friendly data app development platform, has recently integrated with Vizzu's ipyvizzu - an innovative open-source data visualization tool that emphasizes animation and storytelling. This collaboration empowers you to craft and share interactive, animated reports and dashboards that transcend traditional static presentations.\n\nTo maximize our learning time, please come prepared by following the setup steps listed at the end of the tutorial description, allowing us to focus solely on skill-building and progress.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 3462, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/dVCvJYfR38k/maxresdefault.jpg", + "title": "Blackwood & Vidos - Creating Interactive, Animated Reports in Streamlit with Vizzu | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=dVCvJYfR38k" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/chris-hoge-building-an-expert-q-a-bot-with-open-source-tools-and-llms-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/chris-hoge-building-an-expert-q-a-bot-with-open-source-tools-and-llms-pydata-nyc-2023.json new file mode 100644 index 000000000..035d862a3 --- /dev/null +++ b/pydata-new-york-city-2023/videos/chris-hoge-building-an-expert-q-a-bot-with-open-source-tools-and-llms-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://docs.google.com/presentation/d/1u32brOjgg-G2MbMk3i3QULAl5v8by_VR42BET8DPPzU/edit?usp=drive_link\n\nIn this workshop, we'll explore how LangChain, Chroma, Gradio, and Label Studio can be employed as tools for continuous improvement, specifically in building a Question-Answering (QA) system trained to answer questions about an open-source project using domain-specific knowledge from GitHub documentation.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 3596, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://docs.google.com/presentation/d/1u32brOjgg-G2MbMk3i3QULAl5v8by_VR42BET8DPPzU/edit?usp=drive_link", + "url": "https://docs.google.com/presentation/d/1u32brOjgg-G2MbMk3i3QULAl5v8by_VR42BET8DPPzU/edit?usp=drive_link" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/LnBiE0fLVvk/maxresdefault.jpg", + "title": "Chris Hoge - Building an Expert Q&A Bot with Open Source Tools and LLMs | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=LnBiE0fLVvk" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/cliff-kerr-sciris-simplifying-scientific-software-in-python-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/cliff-kerr-sciris-simplifying-scientific-software-in-python-pydata-nyc-2023.json new file mode 100644 index 000000000..9667ea56a --- /dev/null +++ b/pydata-new-york-city-2023/videos/cliff-kerr-sciris-simplifying-scientific-software-in-python-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://docs.google.com/presentation/d/1tXUgSwcqFlWE4fGhuJsj29geo1CZ2ExEQbkTI4Ck6Pg/edit?usp=drive_link\n\nSciris aims to streamline the development of scientific software by making it easier to perform common tasks. Sciris provides classes and functions that simplify access to core libraries of the scientific Python ecosystem (such as NumPy), as well as low-level libraries (such as pickle). Some of Sciris' key features include: ensuring consistent list/array types; allowing ordered dictionaries to be accessed by index; and simplifying parallelization, datetime arithmetic, and the saving and loading of complex objects. With Sciris, users can achieve the same functionality with fewer lines of code, reducing the need to copy-paste recipes from Stack Overflow or follow dubious advice from ChatGPT.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2038, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://docs.google.com/presentation/d/1tXUgSwcqFlWE4fGhuJsj29geo1CZ2ExEQbkTI4Ck6Pg/edit?usp=drive_link", + "url": "https://docs.google.com/presentation/d/1tXUgSwcqFlWE4fGhuJsj29geo1CZ2ExEQbkTI4Ck6Pg/edit?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/FAEt2-57RjQ/maxresdefault.jpg", + "title": "Cliff Kerr - Sciris: Simplifying scientific software in Python | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=FAEt2-57RjQ" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/daniel-goldfarb-adding-your-own-data-apps-to-jupyterlab-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/daniel-goldfarb-adding-your-own-data-apps-to-jupyterlab-pydata-nyc-2023.json new file mode 100644 index 000000000..f445dd65f --- /dev/null +++ b/pydata-new-york-city-2023/videos/daniel-goldfarb-adding-your-own-data-apps-to-jupyterlab-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1jpQc5yvRpHUOkjfWr86zM9EfmgUVoxib/view?usp=drive_link\n\nIn this practical talk about how to extend JupyterLab, we focus on understanding the underlying extension support infrastructure. As we walk through a step-by-step example of creating an app in JupyterLab, we'll learn, among other things, how to launch that app from different places within JupyterLab, how to style our app, and how to pass parameters to our app to modify its behavior. This talk is for anyone who finds themselves doing complex or repetitive tasks and thinks that they, and others, may benefit from integrating those tasks into JupyterLab.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2941, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://drive.google.com/file/d/1jpQc5yvRpHUOkjfWr86zM9EfmgUVoxib/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1jpQc5yvRpHUOkjfWr86zM9EfmgUVoxib/view?usp=drive_link" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/oBrtaRapl1M/maxresdefault.jpg", + "title": "Daniel Goldfarb - Adding Your Own Data Apps to JupyterLab | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=oBrtaRapl1M" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/dharhas-pothina-taming-the-toxic-python-environment-on-your-laptop-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/dharhas-pothina-taming-the-toxic-python-environment-on-your-laptop-pydata-nyc-2023.json new file mode 100644 index 000000000..66bd1dd42 --- /dev/null +++ b/pydata-new-york-city-2023/videos/dharhas-pothina-taming-the-toxic-python-environment-on-your-laptop-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nHave you experienced the frustration of installing a new Python package, only to discover that your existing code and Jupyter notebooks no longer function as expected? Have you found yourself uttering the phrase, \"It works on my computer,\" to a colleague? Have you ever looked at Randal Munroe's five-year-old XKCD comic on Python environments (https://xkcd.com/1987/) and felt torn between laughter and despair?\n\nWell, there's hope on the horizon. In this presentation, we will delve into an open-source tool that enables the creation and management of a set of stable, reproducible, and version-controlled environments right on your laptop, all through an intuitive graphical user interface (GUI).\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2489, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://xkcd.com/1987/", + "url": "https://xkcd.com/1987/" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/zQFOZ89RB1k/maxresdefault.jpg", + "title": "Dharhas Pothina - Taming the toxic python environment on your laptop | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=zQFOZ89RB1k" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/dhasmana-et-al-the-billion-request-content-recommendation-system-challenge-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/dhasmana-et-al-the-billion-request-content-recommendation-system-challenge-pydata-nyc-2023.json new file mode 100644 index 000000000..783f2b74e --- /dev/null +++ b/pydata-new-york-city-2023/videos/dhasmana-et-al-the-billion-request-content-recommendation-system-challenge-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nFor online publications and media sites, recommendation systems play an important role in engaging readers. At Chartbeat, we are actively developing a recommendation system that caters to billions of daily pageviews across thousands of global websites. While conventional discussions frequently highlight the data science and machine learning facets of the system, the cornerstone of a successful application is its system architecture. In this presentation, we will dissect our architectural decisions designed to meet high-performance requirements and share insights gleaned from our journey in scaling up the recommendation system.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2047, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/Kjl40MMTNHM/maxresdefault.jpg", + "title": "Dhasmana et al. - The Billion-Request Content Recommendation System Challenge | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=Kjl40MMTNHM" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/dhaval-patel-how-to-become-a-successful-tech-youtuber-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/dhaval-patel-how-to-become-a-successful-tech-youtuber-pydata-nyc-2023.json new file mode 100644 index 000000000..004f03ac3 --- /dev/null +++ b/pydata-new-york-city-2023/videos/dhaval-patel-how-to-become-a-successful-tech-youtuber-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://docs.google.com/presentation/d/1JWCZ03s5l4AItROouCJNxqPQnGYzEqZI/edit?usp=drive_link&ouid=115185127005110028739&rtpof=true&sd=true\n\nNumerous tech professionals are transitioning to full-time YouTube careers, signifying the platform\u2019s viability beyond a side gig. In this talk, you will get a glimpse of YouTube's impact on data science education and learn about a 5 step framework for becoming a successful tech (or data science) YouTuber.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2373, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://docs.google.com/presentation/d/1JWCZ03s5l4AItROouCJNxqPQnGYzEqZI/edit?usp=drive_link&ouid=115185127005110028739&rtpof=true&sd=true", + "url": "https://docs.google.com/presentation/d/1JWCZ03s5l4AItROouCJNxqPQnGYzEqZI/edit?usp=drive_link&ouid=115185127005110028739&rtpof=true&sd=true" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/dw-QXcQVx2M/maxresdefault.jpg", + "title": "Dhaval Patel - How to Become a Successful Tech YouTuber? | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=dw-QXcQVx2M" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/dobrindt-et-al-synthetic-image-generation-in-rare-disease-diagnosis-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/dobrindt-et-al-synthetic-image-generation-in-rare-disease-diagnosis-pydata-nyc-2023.json new file mode 100644 index 000000000..f8fe1444b --- /dev/null +++ b/pydata-new-york-city-2023/videos/dobrindt-et-al-synthetic-image-generation-in-rare-disease-diagnosis-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nOur talk aims to uncover the Impact of Image Synthetic Data in Disease Diagnosis. Delve into the domain of Generative AI in medical imaging, discover the potential of synthetic data to revolutionize rare disease diagnosis, and explore the ethical and practical considerations surrounding this groundbreaking technology.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1743, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/3kyDfufTPUI/maxresdefault.jpg", + "title": "Dobrindt et al. - Synthetic Image Generation in Rare Disease Diagnosis | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=3kyDfufTPUI" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/erin-mikail-staples-enabling-continuous-deployment-with-stealth-security-smooth-moves-in-mind.json b/pydata-new-york-city-2023/videos/erin-mikail-staples-enabling-continuous-deployment-with-stealth-security-smooth-moves-in-mind.json new file mode 100644 index 000000000..098ef8030 --- /dev/null +++ b/pydata-new-york-city-2023/videos/erin-mikail-staples-enabling-continuous-deployment-with-stealth-security-smooth-moves-in-mind.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nWe\u2019re moving at a speed faster than ever before, with approximately 328.77 million terabytes of data created each day. For those managing these databases, building a secure and sustainable process for building and releasing elements around the core database is more important than ever. In this tutorial; we\u2019ll cover not only the importance and best practices for thinking about this from an architectural perspective but also how to get our hands dirty with building feature flags and a process for enabling continuous iteration and deployment with stealth, security, and smooth moves in mind.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 3386, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/DBmPzTodL1Q/maxresdefault.jpg", + "title": "Erin Mikail Staples - Enabling continuous deployment with stealth, security, & smooth moves in mind", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=DBmPzTodL1Q" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/eswaramoorthy-pothina-from-rags-to-riches-build-an-ai-document-interrogation-app-in-30-mins.json b/pydata-new-york-city-2023/videos/eswaramoorthy-pothina-from-rags-to-riches-build-an-ai-document-interrogation-app-in-30-mins.json new file mode 100644 index 000000000..7a00f2b66 --- /dev/null +++ b/pydata-new-york-city-2023/videos/eswaramoorthy-pothina-from-rags-to-riches-build-an-ai-document-interrogation-app-in-30-mins.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nAs we descend from the peak of the hype cycle around Large Language Models (LLMs), chat-based document interrogation systems have emerged as a high value practical use case. The ability to ask natural language questions and get relevant answers from a large corpus of documents has the potential to fundamentally transform organizations and make institutional knowledge accessible.\n\nRetrieval-augmented generation (RAG) is a technique to make foundational LLMs more powerful and accurate, and a leading way to implement a personal or company-level chat-based document interrogation system. In this talk, we\u2019ll understand RAG by creating a personal chat application. We\u2019ll use a new OSS project called Ragna that provides a friendly Python and REST API, designed for this particular case. We\u2019ll also demonstrate a web application that leverages the REST API built with Panel\u2013a powerful OSS Python application development framework.\n\nBy the end of this talk, you will have an understanding of the fundamental components that form a RAG model as well as exposure to open source tools that can help you or your organization explore and build on your own applications.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2474, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/dhxRO6HdSh0/maxresdefault.jpg", + "title": "Eswaramoorthy & Pothina - From RAGs to riches: Build an AI document interrogation app in 30 mins", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=dhxRO6HdSh0" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/fabio-buso-build-simpler-production-ml-systems-using-feature-training-inference-pipelines.json b/pydata-new-york-city-2023/videos/fabio-buso-build-simpler-production-ml-systems-using-feature-training-inference-pipelines.json new file mode 100644 index 000000000..9eb61e455 --- /dev/null +++ b/pydata-new-york-city-2023/videos/fabio-buso-build-simpler-production-ml-systems-using-feature-training-inference-pipelines.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nThere is a wide array of tools available to simplify the process for data scientists to package their models and deploy them in production, ranging from serverless functions to Docker containers. However, deploying models in production remains a challenge, particularly when it comes to data access.\nReal-time ML systems typically require low-latency access to precomputed features containing history or context data. The code used to create those features should be consistent with the code used to create features using during model training. Similarly, batch ML systems should use the same logic to compute features for training and batch inference.\nThe FTI (Feature, Training, Inference) pipeline architecture is a unified pattern for building batch and real-time ML systems. It enables the independent development and operation of feature pipelines (that transform raw data into features/labels), training pipelines (that take features/labels as input and produce models as output), and inference pipelines (that take model(s) and features as input and produce predictions as output). The pipelines have clear inputs and outputs, and can even be implemented using different technologies (e.g., Spark for feature pipelines, and Python for training and inference pipelines).\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 4298, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/Mna14aTtD8s/maxresdefault.jpg", + "title": "Fabio Buso - Build Simpler Production ML Systems using Feature/Training/Inference Pipelines", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=Mna14aTtD8s" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/florian-jacta-turning-your-data-ai-algorithms-into-full-web-applications-in-no-time-with-taipy.json b/pydata-new-york-city-2023/videos/florian-jacta-turning-your-data-ai-algorithms-into-full-web-applications-in-no-time-with-taipy.json new file mode 100644 index 000000000..af5081042 --- /dev/null +++ b/pydata-new-york-city-2023/videos/florian-jacta-turning-your-data-ai-algorithms-into-full-web-applications-in-no-time-with-taipy.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nNumerous packages exist within the Python open-source ecosystem for algorithm building and data visualization. However, a significant challenge persists, with over 85% of Data Science Pilots failing to transition to the production stage.\n\nThis talk introduces Taipy, an open-source Python library for building web applications\u2019 front-end and back-end. It enables Data Scientists and Python Developers to create production-ready applications for end-users.\n\nIts simple syntax facilitates the creation of interactive, customizable, and multi-page dashboards without having to know about HTML or CSS. Taipy generates highly interactive interfaces, including charts and all sorts of widely used controls.\n\nAdditionally, Taipy is engineered to construct robust and tailored data-driven back-end applications. It models dataflows and orchestrates pipelines. Each pipeline execution is referred to as a scenario. Scenarios are stored, recorded, and actionable, enabling what-if analysis or KPI comparison.\n\nLately, Taipy provides the most suitable cloud tool to host, deploy, and share your Taipy applications easily. In addition, this platform provides the ability to manage, store, and maintain the various states of your backend.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2046, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/V9SWLmJ5myI/maxresdefault.jpg", + "title": "Florian Jacta - Turning your Data/AI algorithms into full web applications in no time with Taipy", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=V9SWLmJ5myI" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/gaston-barbero-basics-of-cloud-computing-for-data-scientists-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/gaston-barbero-basics-of-cloud-computing-for-data-scientists-pydata-nyc-2023.json new file mode 100644 index 000000000..67694e069 --- /dev/null +++ b/pydata-new-york-city-2023/videos/gaston-barbero-basics-of-cloud-computing-for-data-scientists-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://docs.google.com/presentation/d/1EY3UinrDihPSlIdy_Udy6M06LUEiRepsfGJMW93oseY/edit?usp=drive_link\n\nAs data scientists, we are often unaware of what's happening under the hood when our models are put in the corporate cloud environment. If I had to deploy a model to the cloud provider from scratch, what are the options I have? This talk gives an introduction to basic cloud computing concepts and services so next time you will be confident in evaluating the different alternatives for taking your models to the cloud.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1447, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://docs.google.com/presentation/d/1EY3UinrDihPSlIdy_Udy6M06LUEiRepsfGJMW93oseY/edit?usp=drive_link", + "url": "https://docs.google.com/presentation/d/1EY3UinrDihPSlIdy_Udy6M06LUEiRepsfGJMW93oseY/edit?usp=drive_link" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/CdsHVGV6hWk/maxresdefault.jpg", + "title": "Gast\u00f3n Barbero - Basics of cloud computing for data scientists | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=CdsHVGV6hWk" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/gordon-shotwell-tracy-teal-build-simple-and-scalable-apps-with-shiny-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/gordon-shotwell-tracy-teal-build-simple-and-scalable-apps-with-shiny-pydata-nyc-2023.json new file mode 100644 index 000000000..ba6df08ff --- /dev/null +++ b/pydata-new-york-city-2023/videos/gordon-shotwell-tracy-teal-build-simple-and-scalable-apps-with-shiny-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://gshotwell.github.io/shiny-algorithm\n\nThis talk explores the intuitive algorithm behind Shiny for Python and shows how it allows you to scale your apps from prototype to product. Shiny infers a reactive computation graph from your application and uses this graph to efficiently re-render components. This eliminates the need for data caching, state management, or callback functions which lets you build scalable applications quickly.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2073, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://gshotwell.github.io/shiny-algorithm", + "url": "https://gshotwell.github.io/shiny-algorithm" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/9RC8PobU5oQ/maxresdefault.jpg", + "title": "Gordon Shotwell & Tracy Teal - Build Simple and Scalable Apps with Shiny | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=9RC8PobU5oQ" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/hannah-aizenman-plotting-with-matplotlib-telling-static-animated-interactive-stories.json b/pydata-new-york-city-2023/videos/hannah-aizenman-plotting-with-matplotlib-telling-static-animated-interactive-stories.json new file mode 100644 index 000000000..28cd28db6 --- /dev/null +++ b/pydata-new-york-city-2023/videos/hannah-aizenman-plotting-with-matplotlib-telling-static-animated-interactive-stories.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nIn this tutorial we will explore the Palmer Penguins dataset, starting with exploratory charts, then creating a linked animation, and concluding with converting the animation into a simple interactive visualization. In doing so, this tutorial will unpack some of the fundamental concepts that underlie the architecture of Matplotlib, hopefully providing attendees with the foundation for creating effective visualizations using Matplotlib.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 3530, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/f6APC9X8yIM/maxresdefault.jpg", + "title": "Hannah Aizenman - Plotting with Matplotlib; Telling Static, Animated, & Interactive Stories", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=f6APC9X8yIM" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/ines-montani-ryan-wesslen-half-hour-of-labeling-power-can-we-beat-gpt-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/ines-montani-ryan-wesslen-half-hour-of-labeling-power-can-we-beat-gpt-pydata-nyc-2023.json new file mode 100644 index 000000000..c8eed939a --- /dev/null +++ b/pydata-new-york-city-2023/videos/ines-montani-ryan-wesslen-half-hour-of-labeling-power-can-we-beat-gpt-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nLarge Language Models (LLMs) offer a lot of value for modern NLP and can typically achieve surprisingly good accuracy on predictive NLP tasks with a reasonably structured prompt and pretty much no labelled examples. But can we do even better than that? It\u2019s much more effective to use LLMs to create classifiers, instead of using them as classifiers. By using LLMs to assist with annotation, we can quickly create labelled data and systems that are much faster and much more accurate than using LLM prompts alone. In this workshop, we'll show you how to use LLMs at development time to create high-quality datasets and train specific, smaller, private and more accurate fine-tuned models for your business problems.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2716, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/Ta45SfbZNcM/maxresdefault.jpg", + "title": "Ines Montani & Ryan Wesslen - Half hour of labeling power: Can we beat GPT? | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=Ta45SfbZNcM" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/j-j-allaire-keynote-dashboards-with-jupyter-and-quarto-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/j-j-allaire-keynote-dashboards-with-jupyter-and-quarto-pydata-nyc-2023.json new file mode 100644 index 000000000..27d5f6dd7 --- /dev/null +++ b/pydata-new-york-city-2023/videos/j-j-allaire-keynote-dashboards-with-jupyter-and-quarto-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1O_ed6OKEXZBIzKn6yyF9W7f6NaNV-L3J/view?usp=drive_link\n\nKeynote by JJ Allaire\n\nJ.J. is the Founder and CEO of Posit (which you might only know by its previous name, RStudio). J.J. is now leading the Quarto project, a Jupyter-based scientific and technical publishing system. In this talk, J.J. will introduce Quarto Dashboards, an easy way to create production quality dashboards from Jupyter Notebooks. J.J. will also more broadly discuss Posit's recent work in the open source PyData ecosystem along with plans for significantly expanding that work in the future.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2414, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://drive.google.com/file/d/1O_ed6OKEXZBIzKn6yyF9W7f6NaNV-L3J/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1O_ed6OKEXZBIzKn6yyF9W7f6NaNV-L3J/view?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/3HCAScFqr10/maxresdefault.jpg", + "title": "J.J. Allaire - Keynote: Dashboards with Jupyter and Quarto | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=3HCAScFqr10" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/james-powell-simple-simulators-with-pandas-and-generator-coroutines-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/james-powell-simple-simulators-with-pandas-and-generator-coroutines-pydata-nyc-2023.json new file mode 100644 index 000000000..70bf2b9e6 --- /dev/null +++ b/pydata-new-york-city-2023/videos/james-powell-simple-simulators-with-pandas-and-generator-coroutines-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nIn this tutorial, we will review some of the most parts of the Python programming language we don't use every day\u2026 but should! Using the motivating example of a portfolio construction backtester, we will build the rough outline of a library that allows users to design strategies to be automatically executed and evaluated for constructing a portfolio.\nWe will design this tool such that:\n- it has moderate performance for low-frequency strategies (e.g., no intraday trading, no real-time, more mutual fund than hedge fund)\n- it supports high generality in strategy construction\n- it supports \u201cforeign\u201d data (i.e., it minimizes assumptions about pandas.Series or pandas.DataFrame representing market information or trades)\n- it is reasonably easy for a pandas user to construct a strategy without knowing too many esoteric details of Python or pandas (except, of course, the rules of index alignment)\nAlong the way, we will look to answer the following questions:\n- what are generators, generator coroutines, and decorators, and where do they they actually show up in analytical code?\n- why are generators and generator coroutines so well-suited to the design of simulators, backtesters, model training, &c.?\n- how do we write libraries that accept and return pandas.Series that do not lose generality?\n- why is pandas often considered a \u201ctail-end\u201d analytical tool, and how might we solve the problem of writing libraries that may grow a pandas.Series?\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 4903, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/pGGjS6CkDeE/maxresdefault.jpg", + "title": "James Powell - Simple Simulators with pandas and Generator Coroutines | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=pGGjS6CkDeE" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/jonathan-bechtel-forecasting-with-classical-and-machine-learning-methods-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/jonathan-bechtel-forecasting-with-classical-and-machine-learning-methods-pydata-nyc-2023.json new file mode 100644 index 000000000..877d769ea --- /dev/null +++ b/pydata-new-york-city-2023/videos/jonathan-bechtel-forecasting-with-classical-and-machine-learning-methods-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nTraditional time series models such as ARIMA and exponential smoothing have typically been used to forecast time series data, but the use of machine learning methods have been able to set new benchmarks for accuracy in high profile forecasting competitions such as M4 and M5.\n\nHowever, the use of machine learning models can easily lead to inferior results under common conditions. This talk is a discussion of how each of these methods can be used to model time series data, and demonstrate how SKTime provides a unified framework for implementing both families of techniques.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2347, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/QPIimJphFu8/maxresdefault.jpg", + "title": "Jonathan Bechtel - Forecasting With Classical and Machine Learning Methods | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=QPIimJphFu8" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/kewen-gu-anjani-prasad-atluri-how-to-empower-utility-vegetation-management-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/kewen-gu-anjani-prasad-atluri-how-to-empower-utility-vegetation-management-pydata-nyc-2023.json new file mode 100644 index 000000000..9f22d7e06 --- /dev/null +++ b/pydata-new-york-city-2023/videos/kewen-gu-anjani-prasad-atluri-how-to-empower-utility-vegetation-management-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/17LXcunepetJT1jzRu4DIhngINejoIWVS/view?usp=drive_link\n\nThe great majority (more than 2/3) of power outages are caused by contact from vegetation to an active power line, with the added risk of fire and public safety. The goal for utility companies is to manage the vegetation near their above-ground infrastructure in order to reduce these types of contact during inclement weather. This session will discuss an AI-driven vegetation management solution, using LiDAR and satellite imagery to determine the highest risk areas of a utility's service area. Our approach is able to give insights across a service territory, by line down to the foot level as far as how close a branch may be to a power line. This work will enable them to shift from cycle-based to condition-based trimming. We will go over the data used, the various technical challenges, and our approach to scale the solution.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1813, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://drive.google.com/file/d/17LXcunepetJT1jzRu4DIhngINejoIWVS/view?usp=drive_link", + "url": "https://drive.google.com/file/d/17LXcunepetJT1jzRu4DIhngINejoIWVS/view?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/PGfWEtCwm0I/maxresdefault.jpg", + "title": "Kewen Gu & Anjani Prasad Atluri - How to Empower Utility Vegetation Management | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=PGfWEtCwm0I" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/kim-pevey-a-practical-guide-to-analysis-and-interactive-visualization-of-massive-datasets.json b/pydata-new-york-city-2023/videos/kim-pevey-a-practical-guide-to-analysis-and-interactive-visualization-of-massive-datasets.json new file mode 100644 index 000000000..aa8697345 --- /dev/null +++ b/pydata-new-york-city-2023/videos/kim-pevey-a-practical-guide-to-analysis-and-interactive-visualization-of-massive-datasets.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nWhile most scientists aren't at the scale of black hole imaging research teams that analyze Petabytes of data every day, you can easily fall into a situation where your laptop doesn't have quite enough power to do the analytics you need.\n\nIn this hands-on tutorial, you will learn the fundamentals of analyzing massive datasets with real-world examples on actual powerful machines on a cloud provided by the presenter \u2013 starting from how the data is stored and read, to how it is processed and visualized.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 5080, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/zYw8C_hxI-Y/maxresdefault.jpg", + "title": "Kim Pevey - A practical guide to analysis and interactive visualization of massive datasets", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=zYw8C_hxI-Y" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/krishi-sharma-innovation-in-the-age-of-regulation-federated-learning-with-flower-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/krishi-sharma-innovation-in-the-age-of-regulation-federated-learning-with-flower-pydata-nyc-2023.json new file mode 100644 index 000000000..51b28dfe5 --- /dev/null +++ b/pydata-new-york-city-2023/videos/krishi-sharma-innovation-in-the-age-of-regulation-federated-learning-with-flower-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1LDBG-vBI65Hz5vXkVB7E7ZZZmiYy_3hf/view?usp=drive_link\n\nIn the world of machine learning, more data and diverse data sets usually leads to better training, particularly with human centered products such as self-driving cars, IOT devices and medical applications. However, privacy and ethical concerns can make it difficult to effectively leverage many different datasets, particularly in medical and legal services. How can a data scientist or machine learning engineer leverage multiple data sources to train a model without centralizing the data in one place? How can one benefit from multiple datasets without the hassle of breaching data privacy and security?\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1915, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://drive.google.com/file/d/1LDBG-vBI65Hz5vXkVB7E7ZZZmiYy_3hf/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1LDBG-vBI65Hz5vXkVB7E7ZZZmiYy_3hf/view?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/ju5NT3fqoPw/maxresdefault.jpg", + "title": "Krishi Sharma- Innovation in the Age of Regulation: Federated Learning with Flower | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=ju5NT3fqoPw" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/kriti-kohli-leveraging-generative-ai-for-enhanced-e-commerce-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/kriti-kohli-leveraging-generative-ai-for-enhanced-e-commerce-pydata-nyc-2023.json new file mode 100644 index 000000000..2257615dd --- /dev/null +++ b/pydata-new-york-city-2023/videos/kriti-kohli-leveraging-generative-ai-for-enhanced-e-commerce-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nWe take a deep dive into the world of generative AI models and their transformative applications in e-commerce, specifically focusing on the implementation of these models for tasks such as text generation, dynamic and personalized content creation and AI assistants.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2192, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/rBuClSre0xg/maxresdefault.jpg", + "title": "Kriti Kohli - Leveraging Generative AI for Enhanced E-commerce | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=rBuClSre0xg" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/kumar-radha-ghukasyan-covalent-a-new-paradigm-for-high-compute-cloud-workloads.json b/pydata-new-york-city-2023/videos/kumar-radha-ghukasyan-covalent-a-new-paradigm-for-high-compute-cloud-workloads.json new file mode 100644 index 000000000..56356b79b --- /dev/null +++ b/pydata-new-york-city-2023/videos/kumar-radha-ghukasyan-covalent-a-new-paradigm-for-high-compute-cloud-workloads.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://docs.google.com/presentation/d/1JOpAx_hBrWsX6IfmVF-OTNk6Ekoqmw18Ygv_03PQUyw/edit?usp=drive_link\n\nAs the technological landscape evolves from being data-centric to compute-intensive, the challenges in resource allocation, scalability, cost, and workflow complexity have become more pronounced. Traditional cloud tools often fall short in efficiently managing resources like GPUs, and the transition from local to cloud-based environments often involves cumbersome code changes and configurations. Additionally, the high costs and complex workflows associated with compute-intensive tasks are exacerbated by the scarcity and high demand for specialized computing resources. Covalent emerges as a Pythonic framework that addresses these multifaceted challenges. It simplifies the development of compute-intensive products, making them feel like a direct extension of one's local laptop rather than a complex cloud architectural exercise. Moreover, Covalent aids in cost reduction by efficiently managing and allocating resources, thereby optimizing the overall operational expenses. This tutorial will explore how Covalent is uniquely positioned to meet the computational and operational demands of a broad range of high-compute developments, including but not limited to Large Language Models and Generative AI, offering a more efficient and streamlined approach to cloud-based tasks.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 5157, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://docs.google.com/presentation/d/1JOpAx_hBrWsX6IfmVF-OTNk6Ekoqmw18Ygv_03PQUyw/edit?usp=drive_link", + "url": "https://docs.google.com/presentation/d/1JOpAx_hBrWsX6IfmVF-OTNk6Ekoqmw18Ygv_03PQUyw/edit?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/jzAZAGxFphE/maxresdefault.jpg", + "title": "Kumar Radha & Ghukasyan - Covalent: A New Paradigm for High Compute Cloud Workloads", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=jzAZAGxFphE" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/lightning-talks-day-2-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/lightning-talks-day-2-pydata-nyc-2023.json new file mode 100644 index 000000000..dc6501580 --- /dev/null +++ b/pydata-new-york-city-2023/videos/lightning-talks-day-2-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nA PyData NYC tradition. Hosted by Erin Mikail Staples, lightning talks are fast-paced 5-minute talks by conference attendees.\n\nWant to know more about what to expect? Jessica Garson has written up some great advice on how to prepare and make the most of it! https://dev.to/jessicagarson/how-giving-lightning-talks-helped-me-gain-technical-confidence\u20132omm\n\nNo previous knowledge is expected; all levels are welcome to listen or present (limited slots available!).\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1712, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://dev.to/jessicagarson/how-giving-lightning-talks-helped-me-gain-technical-confidence\u20132omm", + "url": "https://dev.to/jessicagarson/how-giving-lightning-talks-helped-me-gain-technical-confidence\u20132omm" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/Ggxx34MOENc/maxresdefault.jpg", + "title": "Lightning Talks Day 2 | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=Ggxx34MOENc" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/liz-johnson-harnessing-test-driven-development-ci-cd-for-smarter-data-analysis-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/liz-johnson-harnessing-test-driven-development-ci-cd-for-smarter-data-analysis-pydata-nyc-2023.json new file mode 100644 index 000000000..9f926d51e --- /dev/null +++ b/pydata-new-york-city-2023/videos/liz-johnson-harnessing-test-driven-development-ci-cd-for-smarter-data-analysis-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1VuVZIk7818u0klznebKN3ZSK2MdmzgpT/view?usp=drive_link\n\nThis talk will focus on applying Test Driven Development principles and practices to data analysis and basic ML Models.\n\nWe will talk about the benefits of unit testing your python scripts and ML engines. We will live code examples of how to build unit tests during data analysis, how we can use fixtures to make basic validation on our ML engines, and once we create a script with the process end-to-end we will look at options for integration testing. Finally, we will set up a github pipeline that will run our tests in different phases in order to give us visibility into the accuracy of our scripts/engines.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2127, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://drive.google.com/file/d/1VuVZIk7818u0klznebKN3ZSK2MdmzgpT/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1VuVZIk7818u0klznebKN3ZSK2MdmzgpT/view?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/nKkmqWf5424/maxresdefault.jpg", + "title": "Liz Johnson - Harnessing Test-Driven Development & CI/CD for Smarter Data Analysis | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=nKkmqWf5424" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/lucas-durand-building-an-interactive-network-graph-to-understand-communities-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/lucas-durand-building-an-interactive-network-graph-to-understand-communities-pydata-nyc-2023.json new file mode 100644 index 000000000..be0888414 --- /dev/null +++ b/pydata-new-york-city-2023/videos/lucas-durand-building-an-interactive-network-graph-to-understand-communities-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://docs.google.com/presentation/d/1wj8fkq6mxcjgCPs78bDmvHLYL-mZZBbWOFPsFGXwWrw/edit?usp=drive_link\n\nPeople are hard to understand, developers doubly so! In this tutorial, we will explore how communities form in organizations to develop a better solution than \"The Org Chart\". We will walk through using a few key Python libraries in the space, develop a toolkit for Clustering Attributed Graphs (more on that later) and build out an extensible interactive dashboard application that promises to take your legacy HR reporting structure to the next level.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 4916, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://docs.google.com/presentation/d/1wj8fkq6mxcjgCPs78bDmvHLYL-mZZBbWOFPsFGXwWrw/edit?usp=drive_link", + "url": "https://docs.google.com/presentation/d/1wj8fkq6mxcjgCPs78bDmvHLYL-mZZBbWOFPsFGXwWrw/edit?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/3LwxyynEUwQ/maxresdefault.jpg", + "title": "Lucas Durand - Building an Interactive Network Graph to Understand Communities | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=3LwxyynEUwQ" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/mars-lee-comics-in-numpy-more-likely-than-you-think-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/mars-lee-comics-in-numpy-more-likely-than-you-think-pydata-nyc-2023.json new file mode 100644 index 000000000..0c195423b --- /dev/null +++ b/pydata-new-york-city-2023/videos/mars-lee-comics-in-numpy-more-likely-than-you-think-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://docs.google.com/presentation/d/17_rh_M0il99JYwTd3Wt4pAhSvUIrPxiz/edit?usp=sharing&ouid=115185127005110028739&rtpof=true&sd=true\n\nReading documentation: what if you could flip through a comic book in your hands, instead of scrolling online? What if you read a story instead of a bullet-point list? What if comics were documentation...?\n\nIs that possible? It sure is! In this talk, we'll dive into the NumPy Contributor Comics, which were completed for Google Season of Docs 2023 (GSOD). Let's get more comics in open source!\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1870, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://docs.google.com/presentation/d/17_rh_M0il99JYwTd3Wt4pAhSvUIrPxiz/edit?usp=sharing&ouid=115185127005110028739&rtpof=true&sd=true", + "url": "https://docs.google.com/presentation/d/17_rh_M0il99JYwTd3Wt4pAhSvUIrPxiz/edit?usp=sharing&ouid=115185127005110028739&rtpof=true&sd=true" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/Gv_Ea94wquM/maxresdefault.jpg", + "title": "Mars Lee - Comics in NumPy? More Likely than You Think! | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=Gv_Ea94wquM" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/martha-norrick-opening-remarks-martha-norrick-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/martha-norrick-opening-remarks-martha-norrick-pydata-nyc-2023.json new file mode 100644 index 000000000..c94984e66 --- /dev/null +++ b/pydata-new-york-city-2023/videos/martha-norrick-opening-remarks-martha-norrick-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nOpen remarks by Martha Norrick, the Chief Analytics Officer of New York City.\n\nMartha is the head of the New York City Office of Data Analytics.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 653, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/PwIDspvLmC0/maxresdefault.jpg", + "title": "Martha Norrick - Opening Remarks: Martha Norrick | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=PwIDspvLmC0" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/matthew-rocklin-spark-dask-duckdb-and-polars-benchmarks-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/matthew-rocklin-spark-dask-duckdb-and-polars-benchmarks-pydata-nyc-2023.json new file mode 100644 index 000000000..e7d81f067 --- /dev/null +++ b/pydata-new-york-city-2023/videos/matthew-rocklin-spark-dask-duckdb-and-polars-benchmarks-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nSpark, Dask, DuckDB, and Polars are popular dataframe tools used at large scale. We benchmark these across a variety of scales (10 GiB to 10 TiB) on both local and cloud architectures with the standard TPC-H benchmark. No project emerges unscathed.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2207, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/DwtbPhbDecQ/maxresdefault.jpg", + "title": "Matthew Rocklin - Spark, Dask, DuckDB, and Polars: Benchmarks | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=DwtbPhbDecQ" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/megan-lieu-machine-learning-in-your-data-warehouse-using-python-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/megan-lieu-machine-learning-in-your-data-warehouse-using-python-pydata-nyc-2023.json new file mode 100644 index 000000000..3e6929e46 --- /dev/null +++ b/pydata-new-york-city-2023/videos/megan-lieu-machine-learning-in-your-data-warehouse-using-python-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nMoving data in and out of a warehouse is both tedious and time-consuming. In this talk, we will demonstrate a new approach using the Snowpark Python library. Snowpark for Python is a new interface for Snowflake warehouses with Pythonic access that enables querying DataFrames without having to use SQL strings, using open-source packages, and running your model without moving your data out of the warehouse. We will discuss the framework and showcase how data scientists can design and train a model end-to-end, upload it to a warehouse and append new predictions using notebooks.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1271, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/c7CPmoZE8hE/maxresdefault.jpg", + "title": "Megan Lieu - Machine Learning in your Data Warehouse using Python | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=c7CPmoZE8hE" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/mei-chen-using-open-source-llm-in-etl-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/mei-chen-using-open-source-llm-in-etl-pydata-nyc-2023.json new file mode 100644 index 000000000..1a3994561 --- /dev/null +++ b/pydata-new-york-city-2023/videos/mei-chen-using-open-source-llm-in-etl-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nThis session will provide a case study of using Llama2-70b to tackle a data transformation friction point in reinsurance underwriting. The final approach of the solution is industry agnostic. We will walk through our thought framework for breaking down a business problem into LLM-able chunks, lay out the explored solutions and best performing method, compare local vs. at scale inference, and how we evaluated the unstructured LLM responses to prevent hallucination and ambiguity in getting structured response.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1751, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/69cq3gWQKgU/maxresdefault.jpg", + "title": "Mei Chen - Using Open Source LLM in ETL | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=69cq3gWQKgU" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/michael-zargham-crafting-reliable-rules-with-robust-control-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/michael-zargham-crafting-reliable-rules-with-robust-control-pydata-nyc-2023.json new file mode 100644 index 000000000..740854cf3 --- /dev/null +++ b/pydata-new-york-city-2023/videos/michael-zargham-crafting-reliable-rules-with-robust-control-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nThis talk explores how we create smarter, more reliable economic policies by using a technique called \u201cRobust Control\u201d. Robust control is a technique from control systems engineering focused on driving desired outcomes even when there is a lot of uncertainty about the circumstances and behaviors of the system these policies endeavor to regulate. These methodology assumes we've developed an incomplete structural model of a systems: parts of the system have well defined and enforceable rules, whereas others are models of phenomena outside of our control, such as user behavior. This talk reviews the application of a Robust Control informed workflow to select the parameters of a pricing algorithm. Code and data will be shared from the design and pre-launch tuning work and we will also use data to demonstrate how the real life deployed system did and did not match our models. The goal of this talk to demonstrate how practices from control engineering can be applied in data science applications, especially those where algorithms make decisions with intent to influence human behavior at the user population level.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1686, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/vr6sIfjGmLQ/maxresdefault.jpg", + "title": "Michael Zargham - Crafting Reliable Rules with Robust Control | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=vr6sIfjGmLQ" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/michelle-gill-keynote-scientific-discovery-from-the-lab-bench-to-the-gpu-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/michelle-gill-keynote-scientific-discovery-from-the-lab-bench-to-the-gpu-pydata-nyc-2023.json new file mode 100644 index 000000000..762b9aaf9 --- /dev/null +++ b/pydata-new-york-city-2023/videos/michelle-gill-keynote-scientific-discovery-from-the-lab-bench-to-the-gpu-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nKeynote by Michelle Gill\n\nScientific discovery is being transformed at all stages by advances in computational methods in\nchemistry and biology. This talk will provide an introduction to the research and development my\nteam does to build BioNeMo, a framework for the the development and use of deep learning\nmodels for drug discovery. It will conclude with a discussion of my transition from structural\nbiologist to machine learning scientist and lessons learned while growing a team from two to 40\ndevelopers.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2130, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/ATo2SzA1Pp4/maxresdefault.jpg", + "title": "Michelle Gill - Keynote: Scientific Discovery: From the Lab Bench to the GPU | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=ATo2SzA1Pp4" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/moussa-taifi-modern-data-pipelines-testing-techniques-a-visual-guide-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/moussa-taifi-modern-data-pipelines-testing-techniques-a-visual-guide-pydata-nyc-2023.json new file mode 100644 index 000000000..f1e6462f8 --- /dev/null +++ b/pydata-new-york-city-2023/videos/moussa-taifi-modern-data-pipelines-testing-techniques-a-visual-guide-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/13Ww13xVPySHYEY8zEFbM3FN6ztJ-x98c/view?usp=drive_link\n\n\"Should I just run it in production to see if it works!\" is a common starting point for many python data engineers. Don't let it be your end point. Any software product deteriorates rapidly without disciplined testing. However, testing data pipelines is a hellish experience for new data developers. Unfortunately, there are somethings that are only learnt on the job. It is a crude reality that data pipeline testing is one of those fundamental skills that gets glossed over during the training of new data engineers. It can be so much more fun to learn about the latest and greatest python data processing library. But how can a new python data engineer transform a patchwork of scripts, into a well engineered data product? Testing is the cornerstone of any iterative development to reach acceptable confidence in the outputs of any data pipeline. This talk will help with an overview of modern data pipelines testing techniques in a visual and coherent game plan.\n\nWhy bother testing data pipelines? Billions of budget dollars regularly rely on the excellence of the data scientists, data engineers, and machine learning engineers behind the countless software data pipelines that inform critical business decisions.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2320, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://drive.google.com/file/d/13Ww13xVPySHYEY8zEFbM3FN6ztJ-x98c/view?usp=drive_link", + "url": "https://drive.google.com/file/d/13Ww13xVPySHYEY8zEFbM3FN6ztJ-x98c/view?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/t1MxfuR2AU0/maxresdefault.jpg", + "title": "Moussa Taifi - Modern Data Pipelines Testing Techniques: A Visual Guide | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=t1MxfuR2AU0" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/nitya-narasimhan-simplifying-data-analysis-with-github-codespaces-jupyter-notebooks-open-ai.json b/pydata-new-york-city-2023/videos/nitya-narasimhan-simplifying-data-analysis-with-github-codespaces-jupyter-notebooks-open-ai.json new file mode 100644 index 000000000..c493d35fd --- /dev/null +++ b/pydata-new-york-city-2023/videos/nitya-narasimhan-simplifying-data-analysis-with-github-codespaces-jupyter-notebooks-open-ai.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nAs web developers, we create large quantities of data (e.g., from test reports and analytics) that require insights for iterative optimization. But how does a JavaScript developer begin their journey into data science? Enter GitHub Codespaces, GitHub Copilot and Open AI. In this talk, I'll share my journey into creating a consistent development and runtime environment with GitHub Codespaces and Jupyter Notebooks, then activating it with Open AI to support an interactive \"learn by exploring\" process that helped me (as a JavaScript developer) skill up on Python and data analysis techniques in actionable ways. I'll walk through a couple of motivating use cases, and demonstrate some projects related to competitive programming and data visualization to showcase these insights in action.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2538, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/wVMwKy1QmTM/maxresdefault.jpg", + "title": "Nitya Narasimhan - Simplifying Data Analysis with GitHub Codespaces, Jupyter Notebooks & Open AI", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=wVMwKy1QmTM" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/patrick-hoefler-dask-tutorial-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/patrick-hoefler-dask-tutorial-pydata-nyc-2023.json new file mode 100644 index 000000000..475a2ecda --- /dev/null +++ b/pydata-new-york-city-2023/videos/patrick-hoefler-dask-tutorial-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nLearn how to parallelize or distribute your Python code. We will start with parallelizing it on your local laptop before we move onto a distributed cluster.\n\nThis tutorial shows how to use Dask, a popular open source framework for parallel computing, to scale Python code. We start with parallelizing simple for loops, and move on to scaling out pandas code.\n\nAlong the way we will learn about concepts like partitioning data and why a good chunksize matters, parallel performance tracking and general metrics that are built into Dask, and managing exceptions and debugging on remote machines.\n\nThis will be a hands-on tutorial with Jupyter notebooks.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 5144, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/wQpdX2KxSbQ/maxresdefault.jpg", + "title": "Patrick Hoefler - Dask tutorial | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=wQpdX2KxSbQ" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/patrick-hoefler-the-arrow-revolution-in-pandas-and-dask-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/patrick-hoefler-the-arrow-revolution-in-pandas-and-dask-pydata-nyc-2023.json new file mode 100644 index 000000000..3aea74ad4 --- /dev/null +++ b/pydata-new-york-city-2023/videos/patrick-hoefler-the-arrow-revolution-in-pandas-and-dask-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1FwjmXH_45BfgJuYqOVxZPfdiZPLMJcDX/view?usp=drive_link\n\nThe pandas library for data manipulation and data analysis is the most widely used open source data science software library. Dask is the natural extension for scaling pandas workloads to more than a single machine. The continuing integration and adoption of Apache Arrow accelerates historical bottlenecks in both libraries.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1878, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://drive.google.com/file/d/1FwjmXH_45BfgJuYqOVxZPfdiZPLMJcDX/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1FwjmXH_45BfgJuYqOVxZPfdiZPLMJcDX/view?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/SatEw8K6x5Y/maxresdefault.jpg", + "title": "Patrick Hoefler - The Arrow revolution in pandas and Dask | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=SatEw8K6x5Y" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/phillip-cloud-gil-forsyth-ibis-a-fast-flexible-and-portable-tool-for-data-analytics.json b/pydata-new-york-city-2023/videos/phillip-cloud-gil-forsyth-ibis-a-fast-flexible-and-portable-tool-for-data-analytics.json new file mode 100644 index 000000000..e2c71875d --- /dev/null +++ b/pydata-new-york-city-2023/videos/phillip-cloud-gil-forsyth-ibis-a-fast-flexible-and-portable-tool-for-data-analytics.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nIbis provides a common dataframe-like interface to many popular databases and analytics tools (BigQuery, Snowflake, Spark, DuckDB, \u2026). This lets users analyze data using the same consistent API, regardless of which backend they\u2019re using, and without ever having to learn SQL. No more pains rewriting pandas code to something else when you run into performance issues; write your code once using Ibis and run it on any supported backend. In this tutorial users will get experience writing queries using Ibis on a number of local and remote database engines.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 4612, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/TyopbrmlZx8/maxresdefault.jpg", + "title": "Phillip Cloud & Gil Forsyth - Ibis: A fast, flexible, and portable tool for data analytics", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=TyopbrmlZx8" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/plonska-plonski-turning-notebook-into-a-web-app-with-mercury-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/plonska-plonski-turning-notebook-into-a-web-app-with-mercury-pydata-nyc-2023.json new file mode 100644 index 000000000..510453c86 --- /dev/null +++ b/pydata-new-york-city-2023/videos/plonska-plonski-turning-notebook-into-a-web-app-with-mercury-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nIn this tutorial, you'll discover how to leverage the MERCURY framework to effortlessly transform your computed notebooks, such as those created in Jupyter Notebook, into interactive web apps, insightful reports, and dynamic dashboards. With no need for frontend expertise, you can effectively communicate your work to non-technical team members. Dive into the world of Python and enhance your notebooks to make your insights accessible and engaging.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2806, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/2qhyn5i9vkc/maxresdefault.jpg", + "title": "P\u0142o\u0144ska & P\u0142o\u0144ski - Turning notebook into a web app with Mercury | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=2qhyn5i9vkc" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/ramon-perez-architecting-data-a-deep-dive-into-the-world-of-synthetic-data-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/ramon-perez-architecting-data-a-deep-dive-into-the-world-of-synthetic-data-pydata-nyc-2023.json new file mode 100644 index 000000000..e93d52e6c --- /dev/null +++ b/pydata-new-york-city-2023/videos/ramon-perez-architecting-data-a-deep-dive-into-the-world-of-synthetic-data-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nFinding good datasets or web assets to build data products or websites with, respectively, can be time-consuming. For instance, data professionals might require data from heavily regulated industries like healthcare and finance, and, in contrast, software developers might want to skip the tedious task of collecting images, text, and videos for a website. Luckily, both scenarios can now benefit from the same solution, Synthetic Data.\n\nSynthetic Data is artificially generated data created with machine learning models, algorithms, and simulations, and this workshop is designed to show you how to enter that synthetic world by teaching you how to create a full-stack tech product with five interrelated projects. These projects include reproducible data pipelines, a dashboard, machine learning models, a web interface, and a documentation site. So, if you want to enhance your data projects or find great assets to build a website with, come and spend 3 fun and knowledge-rich hours in this workshop.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2155, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/W9Tvexmtv3M/maxresdefault.jpg", + "title": "Ramon Perez - Architecting Data: A Deep Dive Into the world of Synthetic Data | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=W9Tvexmtv3M" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/ramon-perez-the-merger-of-machine-learning-music-and-programming-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/ramon-perez-the-merger-of-machine-learning-music-and-programming-pydata-nyc-2023.json new file mode 100644 index 000000000..5060b6fcd --- /dev/null +++ b/pydata-new-york-city-2023/videos/ramon-perez-the-merger-of-machine-learning-music-and-programming-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nFrom music composition with code to style transfer and music generation with machine learning (ML), the intersection of music, programming, and ML is opening up exciting avenues for innovation and creativity. This session will take you through a whirlwind tour of the latest techniques and applications that use code and ML to compose music, generate novel rhythms, and evolve the way we approach audio production. If you want to get started writing code and algorithms that create or enhance music, this session will give you the right tools to begin your journey and continue learning.\n\nFrom music composition with code to style transfer and music generation with machine learning (ML), the intersection of music, programming, and ML is opening up exciting avenues for innovation and creativity. This session will take you through a whirlwind tour of the latest techniques and applications that use code and ML to compose music, generate novel rhythms, and evolve the way we approach audio production. If you want to get started writing code and algorithms that create or enhance music, this session will give you the right tools to begin your journey and continue learning.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 3065, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/FABYfqVXbX8/maxresdefault.jpg", + "title": "Ramon Perez - The Merger of Machine Learning, Music and Programming | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=FABYfqVXbX8" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/randy-au-solving-the-problems-in-front-of-you-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/randy-au-solving-the-problems-in-front-of-you-pydata-nyc-2023.json new file mode 100644 index 000000000..c32733f08 --- /dev/null +++ b/pydata-new-york-city-2023/videos/randy-au-solving-the-problems-in-front-of-you-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1OVKSWJGxaUArFAWLVHC70eR2c8QBdcBL/view?usp=drive_link&resourcekey=0-1NlDit0yowLEjSo-RYPMJw\n\nWe're always told that early optimization is bad, not just for our code but our designs and processes. Yet very few of us are able to find that magical balance between getting things done and doing more background research and design. We're always lured by the siren's call of getting things \"right\" on the first try. This talk is about the process of finding the balance between doing the work and thinking about the work.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1574, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://drive.google.com/file/d/1OVKSWJGxaUArFAWLVHC70eR2c8QBdcBL/view?usp=drive_link&resourcekey=0-1NlDit0yowLEjSo-RYPMJw", + "url": "https://drive.google.com/file/d/1OVKSWJGxaUArFAWLVHC70eR2c8QBdcBL/view?usp=drive_link&resourcekey=0-1NlDit0yowLEjSo-RYPMJw" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/-IOB2wiwloI/maxresdefault.jpg", + "title": "Randy Au - Solving the problems in front of you | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=-IOB2wiwloI" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/ritchie-vink-polars-dataframes-in-the-multi-core-era-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/ritchie-vink-polars-dataframes-in-the-multi-core-era-pydata-nyc-2023.json new file mode 100644 index 000000000..eb1768937 --- /dev/null +++ b/pydata-new-york-city-2023/videos/ritchie-vink-polars-dataframes-in-the-multi-core-era-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nPolars is an OLAP query engine that focusses on the DataFrame use case. Machines have changed a lot in the last decade and Polars is a query engine that is written from scratch in Rust to benefit from the modern hardware.\n\nEffective parallelism, cache efficient data structures and algorithms are ingrained in its design. Thanks to those efforts Polars is among the fastest single node OSS query engines out there. Another goal of polars is rethinking the way DataFrame's should be interacted with. Polars comes with a very declarative and versatile API that enables users to write readable. This talk will focus on how Polars can be used and what you gain from using it idiomatically.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2659, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/tqcudsykOGc/maxresdefault.jpg", + "title": "Ritchie Vink - Polars; DataFrames in the multi-core era | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=tqcudsykOGc" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/ryan-curtin-lightweight-low-overhead-high-performance-machine-learning-directly-in-c.json b/pydata-new-york-city-2023/videos/ryan-curtin-lightweight-low-overhead-high-performance-machine-learning-directly-in-c.json new file mode 100644 index 000000000..bca3101c4 --- /dev/null +++ b/pydata-new-york-city-2023/videos/ryan-curtin-lightweight-low-overhead-high-performance-machine-learning-directly-in-c.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nHow big should a machine learning deployment be? What is a reasonable size for a microservice container that performs logistic regression? Although Python is the generally used ecosystem for data science work, it doesn't provide satisfactory answers to the size question. Size matters: if deploying to the edge or to low-resource devices, there's a strict upper bound on how large the deployment can be; if deploying to the cloud, size (and compute overhead) correspond directly to cost. In this talk, I will show how typical data science pipelines can be rewritten directly in C++ in a straightforward way, and that this can provide both performance improvements as well as massive size improvements, with total size of deployments sometimes in the single-digit MBs.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2590, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/emJyPeoHDjU/maxresdefault.jpg", + "title": "Ryan Curtin - Lightweight, low-overhead, high-performance: machine learning directly in C++", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=emJyPeoHDjU" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/saba-nejad-how-to-use-python-to-better-understand-the-impact-of-electricity-pricing-on-consumption.json b/pydata-new-york-city-2023/videos/saba-nejad-how-to-use-python-to-better-understand-the-impact-of-electricity-pricing-on-consumption.json new file mode 100644 index 000000000..89e00ae05 --- /dev/null +++ b/pydata-new-york-city-2023/videos/saba-nejad-how-to-use-python-to-better-understand-the-impact-of-electricity-pricing-on-consumption.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nElectricity is unique in that its storage is prohibitively costly; this makes it essential for supply to, at least, meet demand at every second of every day. In times of crisis where demand exceeds its projected amount, system operators need to fall back on different methods to lower demand. One such method is Dynamic Pricing which incentivizes customers to lower their consumption by increasing electricity prices during those times. There are trials that test out this pricing model against a flat rate pricing model. This talk uses mathematics and statistical techniques applied in python to see the impact of dynamic pricing on consumption.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2415, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/A2sZfjpcBlo/maxresdefault.jpg", + "title": "Saba Nejad - How to Use Python to Better Understand the Impact of Electricity Pricing on Consumption", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=A2sZfjpcBlo" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/sebastian-benthall-open-source-computational-economics-the-state-of-the-art-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/sebastian-benthall-open-source-computational-economics-the-state-of-the-art-pydata-nyc-2023.json new file mode 100644 index 000000000..e692bc7a0 --- /dev/null +++ b/pydata-new-york-city-2023/videos/sebastian-benthall-open-source-computational-economics-the-state-of-the-art-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/144CVnqK_FwJH3d_izRfmczeylIyFfvK-/view?usp=drive_link\n\nEconomics research has widespread policy and industrial applications. It is rapidly changing due to open source tools. Deep learning techniques have widened the range of models that it is feasible to solve, simulate, and estimate. This talk highlights recent contributions to computational economics and their Python packages. It is aimed at quantitative analysts and economists working in finance and public policy.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1899, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://drive.google.com/file/d/144CVnqK_FwJH3d_izRfmczeylIyFfvK-/view?usp=drive_link", + "url": "https://drive.google.com/file/d/144CVnqK_FwJH3d_izRfmczeylIyFfvK-/view?usp=drive_link" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/GbouF4aXOFk/maxresdefault.jpg", + "title": "Sebastian Benthall - Open Source Computational Economics: The State of the Art | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=GbouF4aXOFk" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/singh-srinivasan-using-generative-ai-and-foundation-models-to-predict-above-ground-biomass.json b/pydata-new-york-city-2023/videos/singh-srinivasan-using-generative-ai-and-foundation-models-to-predict-above-ground-biomass.json new file mode 100644 index 000000000..d85739175 --- /dev/null +++ b/pydata-new-york-city-2023/videos/singh-srinivasan-using-generative-ai-and-foundation-models-to-predict-above-ground-biomass.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1M9-Qo3i0AZSF5hJk6pZdsUGO-x6XqY1r/view?usp=drive_link\n\nA key challenge in training AI models is lack of labeled or ground truth data. This is especially true in the remote sensing field where seasonal changes and differences between label characteristics makes difficult creating a common labeled dataset. With the emergence of self-supervised learning the amount and quality of labeled data can be relaxed but model performance is still of paramount importance. This is especially true for quantifying the sources and sinks of greenhouse gases that drive climate change. In this talk, we present how state of the art AI technologies such as generative AI and Foundation Models can be used to estimate Above Ground Biomass (AGBD) changes due to extraction of CO2 from the atmosphere by vegetation. We demonstrate how these tools can be used by companies with NetZero pledge to quantify, monitor, validate and report their offsetting methodologies and sustainability practices.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2497, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://drive.google.com/file/d/1M9-Qo3i0AZSF5hJk6pZdsUGO-x6XqY1r/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1M9-Qo3i0AZSF5hJk6pZdsUGO-x6XqY1r/view?usp=drive_link" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/RRKdd90uqNk/maxresdefault.jpg", + "title": "Singh & Srinivasan - Using Generative AI and Foundation Models to Predict Above Ground Biomass", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=RRKdd90uqNk" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/soumith-chintala-keynote-ai-the-stuff-built-for-ai-are-they-actually-useful-for-data-science.json b/pydata-new-york-city-2023/videos/soumith-chintala-keynote-ai-the-stuff-built-for-ai-are-they-actually-useful-for-data-science.json new file mode 100644 index 000000000..4bc5ce61f --- /dev/null +++ b/pydata-new-york-city-2023/videos/soumith-chintala-keynote-ai-the-stuff-built-for-ai-are-they-actually-useful-for-data-science.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nKeynote by Soumith Chintala\n\nLet's look at the trendy AI stuff: PyTorch, LLaMa, GPT, GPUs, CUDA, Diffusion, MidJourney, etc. Is any of this actually useful for data science and data engineering? That's the question we'll explore by going through a wild ride across several broad topics from education to efficiency to practicality.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1914, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/ysRuJ5BJeFs/maxresdefault.jpg", + "title": "Soumith Chintala - Keynote: AI & the stuff built for AI - are they actually useful for data science?", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=ysRuJ5BJeFs" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/suri-chen-deciphering-sales-drivers-at-pepsico-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/suri-chen-deciphering-sales-drivers-at-pepsico-pydata-nyc-2023.json new file mode 100644 index 000000000..6901fe8e4 --- /dev/null +++ b/pydata-new-york-city-2023/videos/suri-chen-deciphering-sales-drivers-at-pepsico-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://docs.google.com/presentation/d/1ACQc5D2q85Fb1OIG7XIKYqoZL_3sTXuV/edit?usp=drive_link\n\nAbstract: In this talk, we will explore the world of Media Mix Modeling (MMM) and examine the application of Bayesian and Frequentist regression methods to derive valuable marketing insights. MMM plays a pivotal role in marketing strategy, enabling businesses to measure marketing effectiveness and optimize budget allocation across various channels. The presentation will offer an overview of both Bayesian and Frequentist approaches, comparing their principles and applications within the MMM context. We will present a real-world case, showcasing how these two models were used to deconstruct sales driven by several factors and generate actionable insights. Finally, we will share reflections and recommendations for marketers and data scientists regarding further exploration and adoption of different techniques in MMM, empowering businesses to make informed decisions and effectively allocate their marketing resources.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1747, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + }, + { + "label": "https://docs.google.com/presentation/d/1ACQc5D2q85Fb1OIG7XIKYqoZL_3sTXuV/edit?usp=drive_link", + "url": "https://docs.google.com/presentation/d/1ACQc5D2q85Fb1OIG7XIKYqoZL_3sTXuV/edit?usp=drive_link" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/cTCnzOLVSJ0/maxresdefault.jpg", + "title": "Suri Chen - Deciphering Sales Drivers at PepsiCo | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=cTCnzOLVSJ0" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/thomas-j-fan-scikit-learn-on-gpus-with-array-api-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/thomas-j-fan-scikit-learn-on-gpus-with-array-api-pydata-nyc-2023.json new file mode 100644 index 000000000..9d5336f5c --- /dev/null +++ b/pydata-new-york-city-2023/videos/thomas-j-fan-scikit-learn-on-gpus-with-array-api-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1HTXNRH4ODTq_V1x6R0NEs-ZLRe8uBstv/view?usp=drive_link\n\nScikit-learn was traditionally built and designed to run machine learning algorithms on CPUs using NumPy arrays. In version 1.3, scikit-learn can now run a subset of its functionality with other array libraries, such as CuPy and PyTorch, using the Array API standard. By adopting the standard, scikit-learn can now operate on accelerators such as GPUs. In this talk, we learn about scikit-learn's API for enabling the feature and the benefits and challenges of adopting the Array API standard.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2187, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://drive.google.com/file/d/1HTXNRH4ODTq_V1x6R0NEs-ZLRe8uBstv/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1HTXNRH4ODTq_V1x6R0NEs-ZLRe8uBstv/view?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/c_s8tr1AizA/maxresdefault.jpg", + "title": "Thomas J. Fan - Scikit-learn on GPUs with Array API | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=c_s8tr1AizA" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/valay-dave-building-robust-reactive-ml-systems-in-a-multiplayer-setting-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/valay-dave-building-robust-reactive-ml-systems-in-a-multiplayer-setting-pydata-nyc-2023.json new file mode 100644 index 000000000..fd10a889b --- /dev/null +++ b/pydata-new-york-city-2023/videos/valay-dave-building-robust-reactive-ml-systems-in-a-multiplayer-setting-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://docs.google.com/presentation/d/1RT7Q2xXkOwdS1zjIzC6K9RKezjoTqVk8quHSh9sozf0/edit?usp=drive_link\n\nBuilding ML systems in business settings isn't just about algorithms; it's also about navigating unpredictable data, fostering efficient collaboration, and promoting constant experimentation. This talk delves into Metaflow's solutions to these challenges, spotlighting its event-driven patterns that streamline model training while leveraging infrastructure shared by multiple data-scientists/engineers. Through a hands-on demonstration, we'll showcase how Metaflow facilitates asynchronous training upon new data arrivals for finetuning a state-of-the-art LLM like LLaMAv2 (although the framework is general and widely applicable). Additionally, we'll highlight how multiple developers can seamlessly experiment with various models as new data becomes available.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2118, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://docs.google.com/presentation/d/1RT7Q2xXkOwdS1zjIzC6K9RKezjoTqVk8quHSh9sozf0/edit?usp=drive_link", + "url": "https://docs.google.com/presentation/d/1RT7Q2xXkOwdS1zjIzC6K9RKezjoTqVk8quHSh9sozf0/edit?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/eIKPrF5qEpA/maxresdefault.jpg", + "title": "Valay Dave - Building Robust Reactive ML Systems In A Multiplayer Setting | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=eIKPrF5qEpA" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/viren-bajaj-piero-ferrante-low-er-code-ml-pipelines-with-conduit-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/viren-bajaj-piero-ferrante-low-er-code-ml-pipelines-with-conduit-pydata-nyc-2023.json new file mode 100644 index 000000000..77436b5d0 --- /dev/null +++ b/pydata-new-york-city-2023/videos/viren-bajaj-piero-ferrante-low-er-code-ml-pipelines-with-conduit-pydata-nyc-2023.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nConduit is a Python package and terminal user interface (TUI) designed to streamline the process of building, deploying, and managing machine learning (ML) pipelines on GCP\u2019s Vertex AI platform. Its primary goal is to improve efficiency for data science teams by reducing the time it takes to deploy ML models while observing MLOps best practices.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1329, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/zImXSvzR7jU/maxresdefault.jpg", + "title": "Viren Bajaj & Piero Ferrante - Low(er) Code ML Pipelines with Conduit | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=zImXSvzR7jU" + } + ] +} diff --git a/pydata-new-york-city-2023/videos/will-ayd-faster-sql-with-pandas-and-apache-arrow-pydata-nyc-2023.json b/pydata-new-york-city-2023/videos/will-ayd-faster-sql-with-pandas-and-apache-arrow-pydata-nyc-2023.json new file mode 100644 index 000000000..baef378a4 --- /dev/null +++ b/pydata-new-york-city-2023/videos/will-ayd-faster-sql-with-pandas-and-apache-arrow-pydata-nyc-2023.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nhttps://drive.google.com/file/d/1gFiR-daUkqfClwLvuMtpLRs89uSoG5Lc/view?usp=drive_link\n\npandas has long been known for its robust I/O offerings, which includes commonly used functions for interacting with SQL databases. With the new Apache ADBC drivers, users can expect even better performance and data type management.\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.\n\n00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2476, + "language": "eng", + "recorded": "2023-11-01", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/nyc2023/" + }, + { + "label": "https://drive.google.com/file/d/1gFiR-daUkqfClwLvuMtpLRs89uSoG5Lc/view?usp=drive_link", + "url": "https://drive.google.com/file/d/1gFiR-daUkqfClwLvuMtpLRs89uSoG5Lc/view?usp=drive_link" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "Julia", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "coding", + "how to program", + "learn", + "learn to code", + "python 3", + "scientific programming", + "software" + ], + "thumbnail_url": "https://i.ytimg.com/vi/XhnfybpWOgA/maxresdefault.jpg", + "title": "Will Ayd - Faster SQL with pandas and Apache Arrow | PyData NYC 2023", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=XhnfybpWOgA" + } + ] +}