9 posts
Notes from Harvard CS50 Introduction to AI lectures and projects
9 posts
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Lecture 6: Language
CS50 AI lecture notes on NLP: context-free grammars, n-grams, bag-of-words Naive Bayes, embeddings, word2vec, sequence models, attention, and transformers.
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Lecture 5: Neural Networks
CS50 AI lecture notes on neural networks, activation functions, backpropagation, and convolutional architectures.
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Lecture 4: Learning
CS50 AI lecture notes on nearest neighbors, perceptrons, SVMs, reinforcement learning, and clustering.
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Lecture 3: Optimization
CS50 AI lecture notes on local search, simulated annealing, linear programming, and CSPs.
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Crossword Generator
CS50 AI project notes on solving crosswords as a CSP with heuristics and AC-3.
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Lecture 2: Uncertainty
CS50 AI lecture notes on probabilistic reasoning, Bayes' rule, Bayesian networks, and HMMs.
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Lecture 1: Knowledge
CS50 AI lecture notes on propositional and first-order logic, entailment, and resolution.
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Minesweeper AI
CS50 AI project notes on knowledge-based inference for Minesweeper.
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Lecture 0: Search
CS50 AI lecture notes on search algorithms, from BFS/DFS to A* and minimax.