Learning-AI

This repo lists the recommended materials to learn AI, Machine Learning and Deep Learning

Roadmap

• Taiwan NTHU AI learning roadmap

Search Dataset

• Google Dataset Search
• UCI Dataset

AI

[Textbooks]

• Artificial Intelligence: A Modern Approach

[Open Course]

• CS188: Intro to AI

Deep Learning

[Textbooks]

• Deep Learning, from Ian Goodfellow et al.: This book teaches you the theoritical basics about Deep Learning
• Deep Learning, from 斎藤康毅: I highly recommend this book to those who wants to know how Deep learning work in matrix details.

[Open Course]

• Taiwan NTHU Deep Learning course: This is the best open course I've ever seen. It introduces the math basics of machine learning, learning theory and the cutting edge topics about Deep Learning.

Reinforcement Learning

[Textbooks]

• Reinforcement Learning: An Introduction, 2nd from Sutton
• Algorithms fro Reinfrocement Learning

[Open Course]

• 2015, Reinforcement Learning from David Silver in UCL: David gives the essential introduction about reinforcement learning in this course. The content in this course is sufficient to help you to do research on reinforcement learning if you can understand whole content covered in this course.
• 2017, Fall CS294: Deep Reinforcement Learning in UCB: Solid, Clear and Rich materials focus on "Deep" Reinforcement Learning.

Information Theory

[Textbooks]

• Elements of Information Theory, 2nd from Cover Thomas

Probability and Statistics

[Website]

• Seeing Theory