21 Lessons, Get Started Building with Generative AI

Examples and guides for using the OpenAI API

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs,…

12 Lessons to Get Started Building AI Agents

Anthropic's Interactive Prompt Engineering Tutorial

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Instruct-tune LLaMA on consumer hardware

Anthropic's educational courses

Examples and guides for using the Gemini API

This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for re…

llama3 implementation one matrix multiplication at a time

This repository contains implementations and illustrative code to accompany DeepMind publications

This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed …

FinRL®: Financial Reinforcement Learning. 🔥

[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)

Python training for business analysts and traders

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑‍🔬

Code release for NeRF (Neural Radiance Fields)

Overview and tutorial of the LangChain Library

LLM-powered multiagent persona simulation for imagination enhancement and business insights.

AirLLM 70B inference with single 4GB GPU

CoTracker is a model for tracking any point (pixel) on a video.

Neo4j graph construction from unstructured data using LLMs

Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

Everything you need to know to build your own RAG application

RAGEN leverages reinforcement learning to train LLM reasoning agents in interactive, stochastic environments.

This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.