| Date | Topic | Videos | Due |
|---|
| Thu, Jan 08 | Basic Search | State Spaces | |
| Tue, Jan 13 | Basic Search | Generate-and-Test
BFS | |
| Thu, Jan 15 | Basic Search | Uniform Cost
DFS
DFID | 1 Basic Search |
| Tue, Jan 20 | A* and Friends | Greedy Searching
A*
A* Optimality | 2 More Search |
| Thu, Jan 22 | A* and Friends | A* Completeness
IDA Star | 3 Informed Search |
| Tue, Jan 27 | Game Decision Models | 2-Player Games | |
| Thu, Jan 29 | Game Decision Models | Alpha-Beta Pruning | 7 Minimax |
| Tue, Feb 03 | Expectimax | Expectation
Expectimax
Partial Observability | 8 Alpha/Beta Pruning |
| Thu, Feb 05 | Review Day | | 9 Expectimax |
| Tue, Feb 10 | 6-Week Exam | | |
| Thu, Feb 12 | Markov Decision Processes | MDPs
MDP Reward | |
| Tue, Feb 17 | Markov Decision Processes | Value Iteration
Iteration Example | 10 MDPs |
| Thu, Feb 19 | Catch Up | | |
| Fri, Feb 20 | | | Project 1 |
| Tue, Feb 24 | Reinforcement Learning | Direct Estimation | 11 MDP Iteration |
| Thu, Feb 26 | Reinforcement Learning | Temporal Difference | |
| Tue, Mar 03 | Reinforcement Learning | Q-Learning
Q-Learning Example | 12 Model-Free |
| Thu, Mar 05 | Probability | Bayes Rule
Bayes Example
Combining Evidence
Independence | 13 Q-Learning |
| Tue, Mar 10 | Spring Break | | |
| Thu, Mar 12 | Spring Break | | |
| Tue, Mar 17 | Markov Models | Markov Models (11m)
Chain Example (19m) | 14 Probability |
| Thu, Mar 19 | Markov Models | Hidden Markov Models (21m)
Forward Algorithm (13m) | 18 Chains |
| Tue, Mar 24 | Bayesian Networks | Bayesian Networks (20m)
Inference (22m)
Example Inference (24m) | 19 HMMs |
| Thu, Mar 26 | Bayesian Networks | Example Inf. (again) | quiz |
| Tue, Mar 31 | Review Day | | 20 BN |
| Thu, Apr 02 | 12-Week Exam | | |
| Tue, Apr 07 | Work on Project | | |
| Thu, Apr 09 | Perceptron and Neural Networks | Perceptron (13m)
Properties (12m)
Learning (17m) | |
| Tue, Apr 14 | Perceptron and Neural Networks | Neural Nets (11m)
Gradient (26m)
Properties (10m) | 22 Perceptron |
| Thu, Apr 16 | Linear Regression | Linear Alg (optional review)
Linear Alg 2 (17m)
Gauss Jordan Elimination (13m)
Linear Regression (18m) | 23 Neural Networks |
| Fri, Apr 17 | | | Project 2 |
| Tue, Apr 21 | Overfitting and Regularization | Overfitting (9m)
Regularization (11m) | |
| Thu, Apr 23 | Clustering | Clustering (14m) | 25 Matrix/Regression |
| Tue, Apr 28 | Decision Trees | Decision Trees (5m) | 27 Clustering |
| Thu, Apr 30 | (no class) | | |
| Tue, May 05 | (no class) | | |
| Thu, May 07 | Final Exam @ 1300
Rickover 103 | | |