Schedule (tentative)
| Date | Lecture | Logistics | |
|---|---|---|---|
| 01/08 |
Lecture #1:
Introduction [ slides ] [ marked ] |
||
| 01/10 |
Lecture #2:
Linear Algebra: Coordinate Vectors [ slides ] [ marked ] |
||
| 01/12 |
Lecture #3:
Linear Algebra: Coordinate Vectors [ slides ] [ marked ] |
||
| 01/15 | No Class (MLK holiday) | ||
| 01/17 |
Lecture #4:
Linear Algebra: Linear Transformation [ slides ] [ marked ] |
||
| 01/19 |
Lecture #5:
Linear Algebra: Matrix [ slides ] [ marked ] |
||
| 01/22 |
Lecture #6:
Linear Algebra: Eigenvectors [ slides ] [ marked ] |
||
| 01/24 |
Lecture #7:
Diagonalization [ slides ] [ marked ] |
||
| 01/26 |
Lecture #8:
Diagonalization and PCA [ slides ] [ marked ] |
||
| 01/29 |
Lecture #9:
PCA (I) [ slides ] [ marked ] |
||
| 01/31 |
Lecture #10:
PCA (II) [ slides ] [ marked ] |
||
| 02/02 |
Lecture #11:
PCA (III) [ slides ] [ marked ] |
||
| 02/05 |
Lecture #12:
PCA (IV) [ slides ] [ marked ] |
||
| 02/07 |
Lecture #13:
Nonlinear Dimensionality Reduction [ slides ] [ marked ] |
||
| 02/09 |
Lecture #14:
Laplacian Eigenmaps [ slides ] [ marked ] |
||
| 02/12 |
Lecture #15:
Laplacian Eigenmaps [ slides ] [ marked ] |
||
| 02/14 |
Lecture #16:
Laplacian Eigenmaps [ slides ] [ marked ] |
||
| 02/16 |
Mid-term I
|
||
| 02/19 | No Class (President's Day) | ||
| 02/21 |
Lecture #17:
Linear Model [ slides ] [ marked ] |
||
| 02/23 |
Lecture #18:
Linear Model [ slides ] [ marked ] |
||
| 02/26 |
Lecture #19:
Feature Maps [ slides ] [ marked ] |
||
| 02/28 |
Lecture #20:
RBF Networks [ slides ] [ marked ] |
||
| 03/01 |
Lecture #21:
Neural Networks [ slides ] [ marked ] |
||
| 03/04 |
Lecture #22:
Training Neural Networks [ slides ] [ marked ] |
||
| 03/06 |
Lecture #23:
SGD [ slides ] [ marked ] |
||
| 03/08 |
Lecture #24:
SGD [ slides ] |
||
| 03/11 |
Mid-term II
|
||
| 03/13 |
Lecture #25:
Convolutional Networks [ slides ] |
||
| 03/15 |
Lecture #26:
Autoencoder [ slides ] |