Jan 19 |
Course information |
PDF |
|
|
Jan 24, 26 |
Review on Probability and Linear Algebra |
PDF |
|
HW 01 |
Jan 31, Feb 2 |
Introduction to learning theory |
PDF |
Code |
|
Feb 7, 9 |
Linear predictors |
PDF |
Code |
HW 02 |
Feb 14, 16 |
Linear predictors (II) |
|
|
|
Feb 21, 23 |
Bias-complexity Tradeoff |
PDF |
Code |
|
Feb 28, Mar 2 |
SVMs and kernel methods |
PDF |
Demo |
|
Mar 7, 9 |
No class |
|
|
|
Mar 14, 16 |
SVMs and kernel methods (II) |
|
|
|
Mar 21, 23 |
Model selection and validation |
PDF |
|
HW 03 |
Mar 28, 30 |
Neural networks |
PDF |
Demo |
|
Apr 4, 6 |
Optimization methods |
PDF |
|
|
Apr 11, 13 |
CNNs and RNNs |
PDF |
|
|
Apr 18, 20 |
Dimension Reduction |
PDF |
Code |
|
Apr 25, 27 |
LLMs |
PDF |
Demo |
|
May 2 |
Review |
|
|
Final Project Due |