The schedule is tentative, it will very likely change as we go. Links to the course material will be provided in the schedule below before each class.
The course schedule
Week | Tuesday | Thursday |
---|---|---|
01 | Oct 15 No class |
Oct 17 No class |
02 | Oct 22 Introduction / organization [slides, 8up] |
Oct 24 Linear algebra (vector, matrices) [slides, 8up] |
03 | Oct 29 Linear algebra (dot product) |
Oct 31 Linear algebra (linear transformations) |
04 | Nov 05 Linear algebra (solving systems of equations) |
Nov 07 Linear algebra (matrix inverses, projection, regression) |
05 | Nov 12 Linear algebra (matrix factorization, eigenvalues/vectors, SVD) |
Nov 14 Wrap up |
06 | Nov 19 Calculus (derivatives) |
Nov 21 Calculus (integrals) |
07 | Nov 26 Calculus (finding minima/maxima) |
Nov 28 Probability theory |
08 | Dec 03 Probability theory |
Dec 05 Probability theory |
09 | Dec 10 Information Theory |
Dec 12 Information Theory |
10 | Dec 17 Regression / Wrap up |
Dec 19 ML intro: generalization, bias, variance |
Dec 24 sem. break |
Dec 26 sem. break |
|
Dec 31 sem. break |
Jan 02 sem. break |
|
11 | Jan 07 Logistic regression / Perceptron |
Jan 09 SVM / Naive Bayes / kNN |
12 | Jan 14 Linearity and NN intro |
Jan 16 k-means |
13 | Jan 21 Hierarchical clustering |
Jan 23 Density estimation / EM |
14 | Jan 28 Wrap-up |
Jan 30 Exam |
15 | Feb 04 Exam solutions / discussion |
Feb 06 Practical examples |