Calendar

Jan 30
[Class canceled]
HW0 out
Feb 1
Course overview
slides, red week zine, P&M 1–2 (optional)
Feb 6
Modeling search, backtracking search
slides, goat_partial.py, P&M 3.1–3.4
HW1 out
Feb 8
BFS, DFS, UCS
slides, P&M 3.5
HW0 due
Feb 13
Heuristic search, A*
slides, P&M 3.6
Feb 15
Problem relaxation, adversarial games, minimax game trees
slides, P&M 14.1–14.3
Feb 20
Minimax recurrence, alpha-beta pruning
slides, P&M 14.3
Feb 22
HW0 review :

II. Logic

Feb 27
Boolean algebra, propositional logic, syntax, semantics
notes, P&M 5.1
HW1 due HW2 out
Feb 29
Model checking, inference rules, forward inference with modus ponens, Horn clauses
notes, P&M 5.3, 5.6
Mar 5
Conjunctive normal form, inference by resolution
notes, P&M 5.3
Mar 7
First-order logic
notes, P&M 15.1–15.3
Mar 12
Midterm 1
HW2 due

III. Probabilistic Graphical Models

Mar 14
Exam solutions
Mar 19
From logic to probability, conditional probability, random variables
notes, P&M 9.1
Mar 21
Joint distributions, marginalization, independence, Bayes’ rule
notes, P&M 9.2
HW3 out
Mar 26
–
Mar 28
–
Apr 2
Bayesian networks, conditional independence, explaining away, d-separation
slides
Apr 4
Exact inference by enumeration, forward sampling
slides
Apr 9
Approximate inference, rejection sampling, importance sampling, likelihood weighting
slides, sampling
HW3 due

V. Machine Learning

Apr 11
Supervised learning, empirical risk minimization, decision trees
slides
Apr 16
Fitting decision trees, linear regresion
slides
HW4 out
Apr 18
Multiple linear regression, gradient descent
slides
Apr 23
Training vs. testing, approximation vs. generalization, bias vs. variance
slides
Apr 25
Midterm review
Apr 30
Midterm 2 HW4 due
May 2
Midterm solutions
May 7
Overfitting, regularization
slides
HW5 out

VI. Deep Learning

May 9
Word embeddings, RNNs, transfer learning
May 14
Transformers
May 16
Course conclusion
HW5 due
May 21
Final Exam 10:15 am – 12:15 pm