This repository contains implementations of various basic machine learning models for educational purposes. The project aims to deepen theoretical knowledge through practical implementations.
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src/: Scripts for training and evaluating models.training.py: Training script for the Linear Regression model.
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model/: Scripts for different machine learning models.linear_regression.py: Implementation and training of the Linear Regression model.visualization.py: Functions for visualizing model performance.
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data/: Data-related scripts and files.data_loader.py: Loading and preprocessing datasets.
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requirements.txt: Python packages required for the project. -
.gitignore: Files and directories to be ignored by Git.
Developed collaboratively by Praveen Rangavajhula and Ritvik Singhal to:
- Learn: Deepen understanding of machine learning models.
- Share Knowledge: Benefit from each other's strengths and feedback.
- Divide Tasks: Manage workload effectively.
- Folder Structure: Established and organized.
- Implemented Models: Linear Regression model.
- Visualization: Functions for visualizing model performance.
- Next Steps: Implement additional models, complete data preprocessing, and extend training scripts.