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Best Practices on Recommendation Systems
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
A unified, comprehensive and efficient recommendation library
Fast Python Collaborative Filtering for Implicit Feedback Datasets
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.
An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)
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
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.
A Comparative Framework for Multimodal Recommender Systems
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.
key Deep Learning engineering tricks in recsys