recommendation-system

Best Practices on Recommendation Systems

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

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）

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

本地私有、开源的自进化跨平台 AI 内容发现 Agent：先理解你，再主动从 B站、小红书、抖音、YouTube、X、知乎、Reddit、微博等平台与开放 Web 寻找内容。（支持 deepseek harness 插件） | Local-first open-source cross-platform AI content discovery agent: understands you, then proactively finds content across Bilibili, Xiaohongshu, Douyin, YouTube, X, Zhihu, Reddit, Weibo and the open web.（support deepseek harness plugin）

Pytorch domain library for recommendation 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.

Minimal reproduction of OneRec

A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.

Open CLI for integrating AI search, recommendation, and conversational retrieval into agent systems and business systems

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.

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

A Comparative Framework for Multimodal 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

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.

[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"

Modular e-commerce backend with a GraphQL gateway and gRPC microservices for accounts, products, orders, payments, and recommendations.

A content-based recommender system that recommends movies similar to the movie the user likes and analyses the sentiments of the reviews given by the user

[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"