Documenting my journey as an AI engineer through experiments, readings, interactive explanations, and systems built from scratch.
Introduction to sequential decision-making in reinforcement learning, including agent–environment interaction, rewards, returns, value functions, and Bellman equations with intuitive example.
The story of building a Simple Thoughts Experiments (STE) dataset from scratch.
Understanding the multi-armed bandit problem and how to solve it using reinforcement learning alongwith interactive demo. Chapter 3 of Reinforcement Learning: An Introduction by Sutton and Barto
Understanding how different algorithms plays Tic-Tac-Toe and why RL wins at it. Interactive demo included!
A comprehensive introduction to reinforcement learning from the book : Reinforcement Learning: An Introduction by Sutton and Barto
