This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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Tutorials, assignments, and competitions for MIT Deep Learning related courses.
- deep-learning
- mit
- self-driving-cars
- deep-reinforcement-learning
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.
Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.
- agentic-ai
- langmem
- mcp
- openai-api
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
- agentic-ai
- agentic-rag
- agents
- rag
MongoDB's Generative AI Showcase: an exhaustive collection of examples and sample applications covering Retrieval-Augmented Generation (RAG), AI agents, and industry-specific use cases.
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
- gpu-acceleration
- large-language-models
- llm
- llm-inference
Everything you need to know to build your own RAG application
- agentic-rag
- chatbot
- llm
- machine-learning
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
- cnn
- rnn
- detection
- classification
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
- ai
- chromadb
- cookbooks
- faiss
I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!