从 65,722 个高星开源项目里，
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QRec 是用 Python 编写的学习资料，用于系统学习与查阅，主打速度快。

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

must-read-papers-for-ml 是一个 AI 工具，用于人工智能方向的建模与推理。

Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer

tensorrec 是用 Python 编写的学习资料，用于系统学习与查阅。

A TensorFlow recommendation algorithm and framework in Python.

Transformers4Rec 是用 Python 编写的 AI 工具，用于人工智能方向的建模与推理，主打可扩展。

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.

RecSysDatasets 是用 Python 编写的开源项目，主题标签有限，建议打开仓库查看具体用途。

This is a repository of public data sources for Recommender Systems (RS).

knowledge_graph_attention_network 是用 Python 编写的知识管理工具，用于笔记与知识库整理。

KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019

NVTabular 是用 Python 编写的学习资料，用于系统学习与查阅，主打速度快。

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used…

fastFM 是用 Python 编写的学习资料，用于系统学习与查阅。

fastFM: A Library for Factorization Machines

GNN-Recommender-Systems 是一个学习资料，用于系统学习与查阅。

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

YEDDA 是用 Python 编写的实用工具，用于解决具体场景问题，主打轻量。

YEDDA: A Lightweight Collaborative Text Span Annotation Tool. Code for ACL 2018 Best Demo Paper Nomination.

HugeCTR 是用 C++ 编写的学习资料，用于系统学习与查阅。

HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training

cornac 是用 Python 编写的学习资料，用于系统学习与查阅。

A Comparative Framework for Multimodal Recommender Systems

SASRec 是用 Python 编写的学习资料，用于系统学习与查阅。

SASRec: Self-Attentive Sequential Recommendation