Implicit

This project provides fast Python implementations of several different popular recommendation algorithms for implicit feedback datasets. All models have multi-threaded training routines, using Cython and OpenMP to fit the models in parallel among all available CPU cores. In addition, the ALS and BPR models both have custom CUDA kernels - enabling fitting on compatible GPU’s. This library also supports using approximate nearest neighbour libraries such as Annoy, NMSLIB and Faiss for speeding up making recommendations.

Features

Fast Python Collaborative Filtering for Implicit Datasets
Logistic Matrix Factorization
Bayesian Personalized Ranking
Documentation available
Implicit can be installed from pypi
Examples included

Project Samples

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License

MIT License

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Machine Learning Software

Registered

2024-08-05

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