Reading List
📚 Books
“Deep Work” by Cal Newport
Focus strategies for meaningful productivity |(Summary PDF)
“Range” by David Epstein
Generalists triumph in a specialized world |(Book Summary)
“The Art of Statistics” by David Spiegelhalter
Making data-driven insights clearer |(Author's Site)
“Statistical Methods for Dynamic Treatment Regimes”
Reinforcement Learning, Causal Inference, and Personalized Medicine |Authors: Bibhas Chakraborty, Erica E.M. Moodie
“Introduction to Machine Learning Interviews Book” by Chip Huyen
Copyright ©2021 Chip Huyen
📝 Cheatsheets & Tutorials
🌐 Online Resources
- Distill.pub — Machine Learning Journal
Peer-reviewed ML research explanations
- Andrej Karpathy's AI Blog
Deep learning insights from Tesla's former AI Director
- BAIR Research Blog
UC Berkeley's AI research updates
🎓 Courses
📑 Research Papers
dWOLS: dynamic weighted ordinary least squares
Adel Ahmadi Nadi & Michael Wallace |(Implementation)
Single Stage DTR with Interference
Modelling and estimation for optimal treatment decision with interference | Authors: Lin Su, Rui Song
📰 Articles & Reports
“DeepSeek-R1” Technical Report
Advanced neural embedding techniques |(GitHub Org)
“AlphaFold 2” Nature Paper
Protein structure prediction breakthrough |(Demo)
OpenAI GPT-4 System Card
LLM safety framework |(Official Page)