Best Practices on Recommendation Systems

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference

Fast Python Collaborative Filtering for Implicit Feedback Datasets

A unified, comprehensive and efficient recommendation library

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估

Pytorch domain library for recommendation systems

A TensorFlow recommendation algorithm and framework in Python.

An Open-source Toolkit for Deep Learning based Recommendation with Tensorflow.

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

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

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

A Comparative Framework for Multimodal Recommender Systems

深度学习在推荐系统中的应用及论文小结。

NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.