Microsoft Recommenders

GitHub - microsoft/recommenders: Best Practices on Recommendation Systems

recommenders/sar_movielens.ipynb at main · microsoft/recommenders · GitHub

recommenders · PyPI

recommenders/SETUP.md at main · microsoft/recommenders · GitHub

Dataset module — Microsoft Recommenders 1.1.0 documentation

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We have a new release Recommenders 1.1.0! We have introduced the SASRec and SSEPT algorithms that are based on transformers. In addition, we now have enabled Python 3.8 and 3.9. We have also made improvements on the SARPlus algorithm, including support for Azure Synapse and Spark 3.2. There are also bug fixes and improvements on NCF, RBM, LightGBM, LightFM, Scikit-Surprise, the stratified splitter, dockerfile and upgrade to Scikit-Learn 1.0.2.

Starting with release 0.6.0, Recommenders has been available on PyPI and can be installed using pip!

Here you can find the PyPi page: recommenders · PyPI

Here you can find the package documentation: Recommender Utilities — Microsoft Recommenders 1.1.0 documentation

This repository contains examples and best practices for building recommendation systems, provided as Jupyter notebooks. The examples detail our learnings on five key tasks:

• Prepare Data: Preparing and loading data for each recommender algorithm
• Model: Building models using various classical and deep learning recommender algorithms such as Alternating Least Squares (ALS) or eXtreme Deep Factorization Machines (xDeepFM).
• Evaluate: Evaluating algorithms with offline metrics
• Model Select and Optimize: Tuning and optimizing hyperparameters for recommender models
• Operationalize: Operationalizing models in a production environment on Azure

Several utilities are provided in recommenders to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several state-of-the-art algorithms are included for self-study and customization in your own applications. See the recommenders documentation.

For a more detailed overview of the repository, please see the documents on the wiki page.