Request to Add CoreRec: A Graph-Based Recommendation Engine #42
Description
Dear CoreNet Team,
I am writing to propose the addition of a new recommendation engine, CoreRec, to the CoreNet repository/technology. CoreRec is a cutting-edge recommendation engine specifically designed for graph-based algorithms. It seamlessly integrates advanced neural network architectures and excels in node recommendations, model training, and graph visualizations.
Key Features of CoreRec:
- GraphTransformer Model: A Transformer model tailored for graph data with customizable parameters.
- GraphDataset: A PyTorch dataset for efficient handling of graph data.
- Training Functionality: Comprehensive training functions for various graph-based machine learning models.
- Prediction Capability: Accurate prediction of similar nodes within a graph.
- Graph Visualization: Robust 2D and 3D graph visualization tools.
Benefits of Including CoreRec in CoreNet:
- Enhanced Recommendation Capabilities: Leverage advanced graph algorithms to improve recommendation accuracy.
- Integration with CoreNet: Seamlessly integrate CoreRec's functionalities with existing CoreNet infrastructure.
- Community Collaboration: Foster collaboration and innovation within the CoreNet community by providing a state-of-the-art recommendation engine.
Repository URL: CoreRec GitHub Repository
We believe that CoreRec would be a valuable addition to the CoreNet repository/technology and look forward to your feedback and consideration.
Thank you for your time and attention.
Best regards,
Vishesh Yadav
mail
corerec site