Awesome-AIGC-Tutorials
Curated tutorials and resources for Large Language Models, AI Painting, and more.
https://github.com/luban-agi/Awesome-AIGC-Tutorials
Last synced: 20 days ago
JSON representation
🔊 AI Audio
🌊 Stable Diffusion Principles and Applications
🎨 AI Painting
🧑🎨 Art Fundamentals and AI Painting Techniques
🌊 Stable Diffusion Principles and Applications
💻 AI System
🌊 Stable Diffusion Principles and Applications
- Deep Learning Systems: Algorithms and Implementation - Tianqi Chen, Zico Kolter
- CS 329S: Machine Learning Systems Design - Stanford University
- 15-849: Machine Learning Systems - Carnegie Mellon University
- Computer Science 598D - Systems and Machine Learning - Princeton University
- AI-Sys-Sp22 Machine Learning Systems - University of California, Berkeley
🧠 Deep Learning
🌊 Stable Diffusion Principles and Applications
- Neural Networks/Deep Learning - StatQuest
- Neural Networks - 3Blue1Brown
- Neural Networks: Zero to Hero - Andrej Karpathy
- Practical Deep Learning for Coders - fast.ai
- Deep Learning Specialization - Andrew Ng
- 6.S191: Introduction to Deep Learning - Massachusetts Institute of Technology
- CS25: Transformers United V2 - Stanford University
👋 Introduction
💬 Large Language Models
🔧 LLMs in Practice
- CS25: Transformers United V3 - Stanford University
- LLM Bootcamp - The Full Stack
- Finetuning Large Language Models - DeepLearning.AI
- Learn the fundamentals of generative AI for real-world applications - AWS x DeepLearning.AI
💡 Prompt Engineering
- ChatGPT Prompt Engineering for Developers - DeepLearning.AI - Easy-green)
- Building Systems with the ChatGPT API - DeepLearning.AI
- LangChain for LLM Application Development - DeepLearning.AI
- LangChain: Chat with Your Data - DeepLearning.AI
- Prompt Engineering for ChatGPT - Vanderbilt University
- Prompt Engineering Guide - DAIR.AI
- Learn Prompting
- LangChain AI Handbook - James Briggs and Francisco Ingham
🔬 Theory of LLMs
- 11-667: Large Language Models Methods and Applications - Carnegie Mellon University
- TinyML and Efficient Deep Learning Computing - Massachusetts Institute of Technology
- CS 601.471/671 NLP: Self-supervised Models - Johns Hopkins University
- CS224N: Natural Language Processing with Deep Learning - Stanford University
- Speech and Language Processing - Dan Jurafsky and James H. Martin
- COS 597G (Fall 2022): Understanding Large Language Models - Princeton University
- CS11-711 Advanced Natural Language Processing - Carnegie Mellon University
- CS 601.471/671 NLP: Self-supervised Models - Johns Hopkins University
- CS324 - Advances in Foundation Models - Stanford University
🗂 Miscellaneous
🤝 Friendship Links
✨ Star History
- ![Star History Chart - history.com/#luban-agi/Awesome-AIGC-Tutorials&Date)
- ![Star History Chart - history.com/#luban-agi/Awesome-AIGC-Tutorials&Date)