bookshelf →
Maxim Lapan
Hands on RL
Well-structured guide to the reinforcement learning covering all the essential topics. (600+ pages)
- learning abt modern rl algos like GRPO, PPO, A2C, DDPG, TD3, SAC, etc
- learning abt modern rl algos like GRPO, PPO, A2C, DDPG, TD3, SAC, etc
Sebastian R.
Build a Large language model from scratch ✅
Brilliant book to help you understand and
create your own GPT-like large language models (LLMs) from the ground up (250+ pages)
- learned abt novel components of LLM, fine & instruction tuning & working with data
- learned abt novel components of LLM, fine & instruction tuning & working with data
Tivadar Danka
Mathematics of Machine Learning
Master linear algebra, calculus & probability for ml (650+ pages)
- will learn how maths interlinks with ml :)
- will learn how maths interlinks with ml :)
Jay Alammar
Hands on Large language models ✅
Exceptional guide to the world of language models (500+ pages)
- learned about LLM, prompt engineering, rag, fine tuning
- learned about LLM, prompt engineering, rag, fine tuning
Aurélien Géron
Hands on Machine Learning with Sklearn, Keras, and TensorFlow ✅
The bible of ml (1000+ pages)
- learned tensorflow concepts, deep learning, nlp, rl, llms, gen-ai
- learned tensorflow concepts, deep learning, nlp, rl, llms, gen-ai
Jake VanderPlas
Python Data Science Handbook ✅
Essential Tools for Working with Data (500+ pages)
- learned numpy, pandas, matplotlib, python
- learned numpy, pandas, matplotlib, python
AL Sweigart
Automate the Boring Stuff with Python
✅
Total beginner guide to programming (24+ chapters)
- learned python core concepts, web scrapping & a lot more
- learned python core concepts, web scrapping & a lot more