recommender-system

#自然语言处理#Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

#搜索#高性能、可扩展的向量搜索引擎

#搜索#Weaviate 是一个开源矢量数据库，它同时存储对象和矢量，允许将矢量搜索与结构化过滤与云原生数据库的容错和可扩展性相结合，所有这些都可以通过 GraphQL、REST 和各种语言客户端访问。

#计算机科学#Gorse是一个用Go语言编写的开源推荐系统。Gorse的目标是成为一个通用的开源推荐系统，可以很容易地被引入到各种各样的在线服务中。通过将物品、用户和交互数据导入到Gorse中，系统将自动训练模型，为每个用户生成推荐。

#搜索#Developer-friendly, embedded retrieval engine for multimodal AI. Search More; Manage Less.

#计算机科学#RSTutorials: A Curated List of Must-read Papers on Recommender System.

#面试#推荐系统入门教程，在线阅读地址：https://datawhalechina.github.io/fun-rec/

#计算机科学#A Python implementation of LightFM, a hybrid recommendation algorithm.

#计算机科学#Papers on Computational Advertising

#计算机科学#Fast Python Collaborative Filtering for Implicit Feedback Datasets

#计算机科学#Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.

#自然语言处理#深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI

#计算机科学#Classic papers and resources on recommendation

#自然语言处理#Accelerated deep learning R&D

An index of algorithms for learning causality with data

#搜索#Fast Open-Source Search & Clustering engine × for Vectors & Arbitrary Objects × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍

#计算机科学#Deep recommender models using PyTorch.

#自然语言处理#📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.

#计算机科学#This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

#计算机科学#A Deep Learning Recommender System