Notes

Lecture Notes and Handouts!

These notes collect the course lecture handouts and notebooks. Notebook entries open as rendered Webifier pages with author credits and comments; PDF entries open as static handouts.

Lecture Content
Lecture 1 Intelligent Agents
Intelligent Agents, Fall 2021
Lecture 2 Uninformed Search
Lecture 3 Informed Search
Lecture 4 Advanced Heuristics
Advanced Heuristics Notes
Lecture 5 Local Search
Lecture 6 Search in Continuous Space
Lecture 7 Constraint Satisfaction Problems
Constraint Satisfaction Problems Notes
Lecture 8 Adversarial Search
Adversarial Search Notes
Lecture 9 Bayesian Networks, Part 1
Bayesian Networks, Part 2
Bayesian Networks, Part 3
Bayesian Networks Representation Notes
Lecture 10 Exact Inference in Bayesian Networks
Approximate Inference in Bayesian Networks
Lecture 11 Temporal Probability Models, Part 1
Temporal Probability Models, Part 2
Temporal Probability Models, Part 3
Temporal Probability Models, Part 4
Lecture 12 Hidden Markov Models
Introduction to Machine Learning
Lecture 13 Decision Tree Learning
Lecture 14 Regression
Lecture 15 Neural Networks and MLPs
Lecture 16 Deep Neural Networks and CNNs
Deep Neural Networks: Convolutional Models
Lecture 17 Markov Decision Processes
Lecture 18 Reinforcement Learning
Lecture 19 Introduction to Markov Decision Processes
Lecture 21 Reinforcement Learning Notes
Lecture 22 Reinforcement Learning, Part 2