[Updated on 2025-09-27]
Despite that today information on ML is everywhere, I think there is too much noise. This is a collection of resources that I find useful for understanding the “why” behind the code.
Courses
- Stanford CS336 - Language Modeling From Scratch
- Stanford CS324 - CS324 - Large Language Models
- Harvard CS197 - Dive into dev tools like Pytorch, and HF
- Stanford CS231n - Stanford CS class on CNN for Visual Recognition
- fast.ai - Making neural nets uncool again.
- Effective MLOps with W&B - Effective MLOps: Model Development course
- Made With ML - MLOps course
Deep Learning & Reinforcement Learning
- Reinforcement Learning: An Introduction (Sutton & Barto) - The foundational textbook for RL.
- Modern Robotics (Lynch & Park) - Mechanics, planning, and control.
- Underactuated Robotics (Russ Tedrake) - Algorithms for walking, running, swimming, and flying.
- Probabilistic Robotics (Thrun, Burgard, Fox) - SLAM and robot perception.
- Reinforcement Learning Course - David Silver - The gold standard for RL theory.
- Speech and Language Processing (stanford.edu) - The bible of NLP.
- Deep learning Cheat sheet - Summary of concepts by Stanford researchers.
- google-research/tuning_playbook - Maximizing performance of DL models.
- Gymnasium Documentation (farama.org) - OpenAI Gym agents.
- Proximal Policy Optimization (openai.com) - PPO algorithm for RL.
- Bullet Real-Time Physics Simulation - Physics simulation for robotics.
- Data Version Control · DVC - Version control for ML development.
- MLflow - Managing the ML lifecycle.
LLM Era
- Unsloth Fine-tuning LLMs Guide - Basics and best practices of fine-tuning.
- TRL – Hugging Face - Train language models with RL.
- llama.cpp - LLM inference in C++.
- Lil’Log (lilianweng.github.io) - OpenAI researcher’s blog.
- eugeneyan - LLM systems and engineering.
- Jay Alammar - Visualizing ML and LLM concepts.
- The AiEdge Newsletter - MLOps articles.
- Blog - neptune.ai - Applied ML and experiment tracking.
Math & Physics Foundations
- 3Blue1Brown (YouTube) - The best visual intuition for math.
- Real Analysis - Francis Su - A clear and enthusiastic introduction to analysis.
- Nonlinear Dynamics and Chaos - Steven Strogatz - Lectures on chaos theory and dynamical systems.
- Infinite Powers - How Calculus Reveals the Secrets of the Universe.
- Understanding Analysis - A rigorous and intuitive approach to analysis.
- Topology - The standard text for topology.
- Linear Algebra Done Right - A text that focuses on the structure of linear operators.
- Linear Algebra and Its Applications - A classic text on linear algebra.
- An Introduction to Hilbert Space - Foundation for functional analysis.
- A Visual Introduction to Differential Forms and Calculus on Manifolds - Geometric approach to calculus on manifolds.
- The Information - A History, a Theory, a Flood.
Math & Optimization
- Convex Optimization (Boyd & Vandenberghe) - The bible of optimization in engineering.
- Dynamic Programming and Optimal Control (Bertsekas) - The rigorous foundation for RL.
- An Introduction to Genetic Algorithms (Melanie Mitchell) - Classic intro to evolutionary computation.
- Understanding Deep Learning, by Simon J.D. Prince - Deep Learning notes.
- Introduction to Statistical Learning - Classic statistical learning book.
- Introduction to Probability Models - Sheldon M. Ross - Probability models foundations.
- Optimization with PuLP - Linear programming in Python.
- OR-Tools | Google Developers - Combinatorial optimization.
Software Development
- Developer Roadmaps - roadmap.sh
- jwasham/coding-interview-university - CS study plan.
- LeetCode - Technical interview preparation.
- Advent of Code - Programming puzzles.
- NeetCode Roadmap - Roadmap for LeetCode practice.
- Corey Schafer - Youtube - Python tutorials.
- TheAlgorithms/Python - Algorithms implemented in Python.
- The Modern JavaScript Tutorial - Learn JS.
Extras
- Motion Canvas - Programmatic complex idea visualization.
- 3b1b/manim - Math animation engine.
- Typst - Modern Rust-based alternative to LaTeX.
- Modelling in Blender a Human Hand - Topology guides for 3D.
Good Read!