Top 10 Python Recommender System Projects

implicit

3 3,420 6.2 Python

Fast Python Collaborative Filtering for Implicit Feedback Datasets
RecBole

3 3,163 8.4 Python

A unified, comprehensive and efficient recommendation library

Project mention: RecBole – A unified, comprehensive and efficient recommendation library | news.ycombinator.com | 2024-01-17

WorkOS

workos.com sponsored

The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
spotlight

0 2,934 0.0 Python

Deep recommender models using PyTorch. (by maciejkula)
ranking

1 2,713 6.3 Python

Learning to Rank in TensorFlow
TensorRec

0 1,250 0.0 Python

A TensorFlow recommendation algorithm and framework in Python.
fastFM

0 1,063 0.0 Python

fastFM: A Library for Factorization Machines
NeuRec

2 1,031 0.0 Python

Next RecSys Library
InfluxDB

www.influxdata.com sponsored

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
ranx

1 325 6.7 Python

⚡️A Blazing-Fast Python Library for Ranking Evaluation, Comparison, and Fusion 🐍

Project mention: Sparse Vectors in Qdrant: Pure Vector-based Hybrid Search | dev.to | 2024-02-19

Ranx is a great library for mixing results from different sources.

MAERec

1 48 4.6 Python

[SIGIR'2023] "MAERec: Graph Masked Autoencoder for Sequential Recommendation"

Project mention: Graph Masked Autoencoder for Sequential Recommendation | /r/BotNewsPreprints | 2023-05-09

While some powerful neural network architectures (e.g., Transformer, Graph Neural Networks) have achieved improved performance in sequential recommendation with high-order item dependency modeling, they may suffer from poor representation capability in label scarcity scenarios. To address the issue of insufficient labels, Contrastive Learning (CL) has attracted much attention in recent methods to perform data augmentation through embedding contrasting for self-supervision. However, due to the hand-crafted property of their contrastive view generation strategies, existing CL-enhanced models i) can hardly yield consistent performance on diverse sequential recommendation tasks; ii) may not be immune to user behavior data noise. In light of this, we propose a simple yet effective graph masked autoencoder that adaptively and dynamically distills global item transitional information for self-supervised augmentation. It naturally avoids the above issue of heavy reliance on constructing high-quality embedding contrastive views. Instead, an adaptive data reconstruction paradigm is designed to be integrated with the long-range item dependency modeling, for informative augmentation in sequential recommendation. Extensive experiments demonstrate that our method significantly outperforms state-of-the-art baseline models and can learn more accurate representations against data noise and sparsity. Our implemented model code is available at https://github.com/HKUDS/GMRec.

reco-model-monitoring

1 3 0.0 Python

fastapi + prometheus + grafana 💣

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2024-02-19.