🦜🔗 Build context-aware reasoning applications

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

12 Weeks, 24 Lessons, AI for All!

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

This is a repo with links to everything you'd ever want to learn about data engineering

10 Weeks, 20 Lessons, Data Science for All!

A simple screen parsing tool towards pure vision based GUI agent

A guidance language for controlling large language models.

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

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 mode…

💿 Free software that works great, and also happens to be open-source Python.

Anthropic's educational courses

This repository provides tutorials and implementations for various Generative AI Agent techniques, from basic to advanced. It serves as a comprehensive guide for building intelligent, interactive A…

Examples and guides for using the Gemini API

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

Official inference library for Mistral models

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

Deploy serverless AI workflows at scale. Firebase for AI agents

A Bulletproof Way to Generate Structured JSON from Language Models

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

Genome modeling and design across all domains of life

Everything you need to know to build your own RAG application

📚 Jupyter notebook tutorials for OpenVINO™

Face Depixelizer based on "PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models" repository.

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

This series will take you on a journey from the fundamentals of NLP and Computer Vision to the cutting edge of Vision-Language Models.

Mastering Applied AI, One Concept at a Time

Official implementation of the paper "Watermark Anything with Localized Messages"