instructor: Dave Kauchak
e-mail: [first_name][last_name]@pomona.edu
office hours: TBA
Mon - Thu: 2:30 - 3:30pm (via zoom, link in sakai)
and by appointment
time: T/Th 1:15-2:30pm
location: SCOM 102 (Seaver Commons)
web page: http://www.cs.pomona.edu/classes/cs158/
textbook:
| Date | Topic | Reading | Assignment | Due |
|---|---|---|---|---|
| 1/18 | introduction (ppt) | Ch 1-2 | Assignment 1 (.tex) | 1/21 @ 5pm |
| 1/20 | decision trees (ppt) | Tan Ch 4.3-4.3.5 | ||
| 1/25 | geometric view of data (ppt) | Ch 3 (3.4 optional) | Assignment 2 (.tex) | 1/30 @ 11:59pm |
| 1/27 | perceptron (ppt) | Ch 4 | ||
| 2/1 | features (ppt) | Ch 5-5.4 | Assignment 3 (.tex) | 2/6 @ 11:59pm |
| 2/3 | evaluation (ppt) | Ch 5.5-5.9 | ||
| 2/8 | imbalanced data (ppt) | Ch 6-6.1 | Assignment 4 (.tex) | 2/13 @ 11:59pm |
| 2/10 | beyond binary classification (ppt) | Ch 6-6.3 | ||
| 2/15 | gradient descent (ppt) | Ch 7-7.5 (7.6 optional) | Assignment 5 (.tex) | 2/20 @ 11:59pm |
| 2/17 | regularization (ppt) | |||
| 2/22 | large margin classifiers (ppt) | Ch 7.7 | Assignment 6 (.tex) | 3/1 @ 11:59pm |
| 2/24 | SVM lab | |||
| 3/1 | probability basics (ppt) | Optional: Movallen pgs 7-23 | ||
| 3/3 | probabilistic models (ppt) | Ch 9-9.5 | Assignment 7 (.tex) | Part A: 3/6 @ 11:59 Part B: 3/11 @ 5pm |
| 3/8 | priors and logistic regression (ppt) | Ch 9.6-9.7 | ||
| 3/10 | neural networks (ppt) | Ch 10 | ||
| 3/15 | spring break | |||
| 3/17 | spring break | |||
| 3/22 | backpropagation (ppt) | Optional: backprop example | Assignment 8 (.tex) | 4/3 @ 11:59 |
| 3/24 | deep learning (ppt) | word vectors | ||
| 3/29 | deep learning 2 | |||
| 3/31 | big data (ppt), hadoop | |||
| 4/5 | MapReduce | Assignment 9 (.tex) | Part A: 4/10 @ 11:59pm Part B: 4/17 @ 11:59pm | |
| 4/7 | advanced MapReduce | |||
| 4/12 | final project discussion | Ch 13 | final project | |
| 4/14 | ensemble learning (ppt) | |||
| 4/19 | k-means (ppt) | Ch 3.4, 15-15.1 | ||
| 4/21 | clustering (ppt) | Ch 16 | ||
| 4/26 | ML ethics | paper 1, paper 2, article 1, article 2 | ||
| 4/28 | work session | |||
| 5/3 | project presentations |
Exam schedule: