recommenders-team/recommenders
🏗️ Frameworkrecommenders-team
Best practices and examples for building recommendation systems in Python.
The Recommenders repository by Microsoft offers a comprehensive collection of best practices and tools for building recommendation systems. It includes implementations of various algorithms such as Alternating Least Squares (ALS), Neural Collaborative Filtering (NCF), and Wide & Deep Learning, along with utilities for data splitting, evaluation metrics (RMSE, MAE, precision, recall), and hyperparameter tuning. The project emphasizes operationalization, providing guides for deploying models on Kubernetes and Azure Machine Learning. It also features a set of Jupyter notebooks that walk through the entire workflow from data preprocessing to model serving. The library supports both classical and deep learning methods, making it suitable for both beginners and experts in recommendation systems.
💡Highlights
- ├─21.8k GitHub stars, 3.3k forks
- ├─Best practices for 8+ recommendation algorithms
- └─Includes Jupyter notebooks and Kubernetes deployment guide
🎯For
- ├─Data scientists
- ├─ML engineers
- └─Researchers