Major Topics Covered
Algorithms and representations for artificial intelligence
- Reasoning under uncertainty
- Probability review
- Bayes nets and Markov random fields
- HMMs and query planing
- Introduction to machine learning
- Regression and Classification
- Unsupervised learning
- Neural/deep learning
- Decisions
- MDPs, POMDPs, reinforcement learning, deep RL
- Game theory and linear programming
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