Public repo with summaries, design decisions, and results from my problem sets in CS50’s Introduction to AI with Python.
Each folder includes a README.md with goals, design decisions, and results.
| Project | Lecture | Main Topic | Techniques/Algorithms |
|---|---|---|---|
| degrees/ | Search | Graph search | BFS, shortest path |
| tictactoe/ | Search | Adversarial search | Minimax, pruning |
| knights/ | Knowledge | Knowledge & logic | Propositional KB, model checking |
| minesweeper/ | Knowledge | Knowledge & logic | Propositional KB, inference |
| pagerank/ | Uncertainity | Probabilistic reasoning | Random walk, iterative method |
| heredity/ | Uncertainity | Bayesian networks | Conditional probability, inference |
| crossword/ | Optimization | CSP | AC-3, backtracking, heuristics |
| shopping/ | Learning | Classical ML | KNN, metrics |
| nim/ | Learning | Reinforcement learning | Q-learning |
| traffic/ | Neural Networks | Computer vision | CNN (Keras/TensorFlow) |
| parser/ | Language | NLP | Grammars & parsing |
| questions/ | Language | Retrieval & QA | TF-IDF/BM25 |