Useful and Insightful Machine Learning Websites
22 Dec 2022< 목차 >
- update: 22. 12. 22 (YY. MM. DD)
ML, DL, RL Fundamentals
Books
- PRML, 2006. (Christopher Bishop)
- Computer vision: models, learning, and inference, 2012. (Simon J.D. Prince)
- Deep Learning, 2016. (Ian Goodfellow and Yoshua Bengio and Aaron Courville)
- Understanding Deep Learning, 2023. (Simon J.D. Prince)
Labs
- Bekreley Aritificial Intelligence Research (BAIR)
- Stanford AI Lab (SAIL)
- Stanford Ermon Group
- KAIST ALIN-LAB
- MIT MadryLab
- MLCMU -Blog
Personal Blogs
- The Gradient
- Lil’Log
- Distill
- Yarin Gal’s Blog
- Yang Song’s Blog
- Shervine Amidi’s Blog
- colah’s Blog
- Andrej Karpathy’s Blog
- Lena Voita’s Blog
- Martin Krasser’s Blog
- Shervine Amidi’s Cheatsheets
- Stephen Wolfram
Industry Blogs
- Meta AI
- DeepMind
- OpenAI
- Apple
- Amazon
Lecture and Seminar (Videos)
- Berkeley RAIL LAB Courses
- Deepmind Courses
- Stanford Courses
- MIT 6.S192: Deep Learning for Art, Aesthetics, and Creativity
- AMI Lab POSTECH (Youtube)
- Summer Schools
Others
