Popular GitHub Repositories for Collaborative Innovation

Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.

Gorse open source recommender system engine

The world’s first real-time, distributed, cloud-edge collaborative multimodal AI Agent Framework that simultaneously supports C/C++/Go/Python/JS/TS

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.

The best apps in the AI era aren’t solo experiences—they’re collaborative. Liveblocks provides customizable pre?built features to make your product multiplayer, engaging, and AI?ready. All without derailing your roadmap.

A unified, comprehensive and efficient recommendation library

A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.

A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

Neural Collaborative Filtering

Deep learning for recommender systems

:closed_book: Clarity in the current fast-paced mess of Open Source innovation

Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.

Factorization Machine models in PyTorch

YEDDA: A Lightweight Collaborative Text Span Annotation Tool. Code for ACL 2018 Best Demo Paper Nomination.

Next RecSys Library

The collaborative spreadsheet for AI. Chain cells into powerful pipelines, experiment with prompts and models, and evaluate LLM responses in real-time. Work together seamlessly to build and iterate on AI applications.

? Stateful Serverless That Runs Anywhere. The easiest way to build stateful, AI agent, collaborative, or local-first applications. Deploy to Rivet, Cloudflare, Bun, Node.js, and more.

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