Popular GitHub Repositories for How Computers Work

A natural language interface for computers

Learn how to design, develop, deploy and iterate on production-grade ML applications.

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

Build and share delightful machine learning apps, all in Python. ? Star to support our work!

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.

The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. It showcases practical applications and provides links to open-source projects for implementation, illustrating how AI agents are transforming sectors such as healthcare, finance, education, retail, and more.

Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services

This is a collection of tutorials for learning how to use Docker with various tools. Contributions welcome.

Example ? Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using ? Amazon SageMaker.

[ICLR 2025] Agent S: an open agentic framework that uses computers like a human

A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.

Transformer Explained Visually: Learn How LLM Transformer Models Work with Interactive Visualization

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.

A workshop that teaches you how to build your own coding agent. Similar to Roo code, Cline, Amp, Cursor, Windsurf or OpenCode.

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

? ????? for ???? how to ????? an end-to-end ??????????-????? ??? & ??? ?????? using ?????? best practices: ~ ?????? ???? + 12 ?????-?? ???????

A collection of sample apps to demonstrate how to use Google's ML Kit APIs on Android and iOS

Explore how machine learning works, live in the browser. No coding required.

Like Manus, Computer Use Agent(CUA) and Omniparser, we are computer-using agents.AI-driven local automation assistant that uses natural language to make computers work by themselves

Set of use cases demonstrating how to build AI-featured applications.