π Study Notes
Open-source lecture notes, concept wikis, and exercises for MSc Artificial Intelligence at the University of Amsterdam.
Courses
Reinforcement Learning
Sutton & Barto + UvA lecture series. Covers MDPs, dynamic programming, Monte Carlo, TD learning, function approximation, and deep RL.
β Browse RL lectures Β· Exercises Β· Coding assignments
Information Retrieval
Classical and neural retrieval models. BM25, language models, evaluation metrics, dense retrieval, learned sparse retrieval, and generative IR.
β Browse IR lectures Β· Assignments
Concepts
The Concepts folder is a flat wiki of ~130 interconnected notes spanning both courses. Each concept links to the lectures where it appears and to related concepts. Use the graph view or backlinks to explore connections.
How to use these notes
- Search (Ctrl/Cmd+K) to find any topic
- Graph view to explore how concepts connect
- Backlinks at the bottom of each page show what links here
- All formulas are in LaTeX, all definitions use callouts
About
Built by StanisΕaw Wasilewski using Obsidian + Quartz. Notes are designed to fully substitute lecture attendance β every formula explained term-by-term, every figure reproduced.
Source: GitHub