Concepts and Foundations
- Dive into Deep Learning is an interactive deep learning book with code, math, and discussions
- Deep Learning Tutorial for Beginners provides 18 lessons in Deep Learning
- Introduction to Machine Learning provides introductory lectures on ML
- Reinforcement Learning Lecture Series 2021 provides a comprehensive introduction to modern reinforcement learning, created in collaboration with University College London (UCL)
- The Journey of Open AI GPT models goes over the 2 years long evolution of OpenAI GPT models ending in 2020
- Everything We Know About GPT-4 summarizes prior and current GPT models and OpenAI’s plans for GPT-4
- Illustrated Cheatsheets for Stanford’s AI, Machine Learning, and Deep Learning courses
- How does in-context learning work? provides a plausible explanation of this emergent behavior
- What Is ChatGPT Doing … and Why Does It Work? explains how ChatGPT, and LLMs in general, work
- Prompt Engineering explains the term and the known variations for autoregressive language models
- Five years of GPT progress shows how GPTs have evolved over time
- Practical Deep Learning is a free course for people with coding experience to learn how to apply deep learning and machine learning to practical problems
- What Are Transformer Models and How Do They Work? provides a simple conceptual introduction to Transformer Models