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

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

Fast Python Collaborative Filtering for Implicit Feedback Datasets

A unified, comprehensive and efficient recommendation library

Pytorch domain library for recommendation systems

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

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.

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.

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

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

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

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.

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

A Comparative Framework for Multimodal Recommender Systems

key Deep Learning engineering tricks in recsys

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.