Machine Learning and Data Mining
Assignments
Here are the assignments for CMPS 142, Spring 2017
Homework:
| # | Due | Files | Sample solution |
| 1 | 4/20 | Homework 1 (Updated on 04/12) | |
| 2 | 5/2 | Homework 2 | |
| 3 | 5/16 | Homework 3 | |
| 4 | 5/30 |
Spambase file (remove .txt extension) |
|
| 5 | 6/8 |
Reading Assignments:
| Due | |
| 1st Week | Ng notes: Lecture Notes 1, Part I, Chapter 1 |
| 2nd Week |
Ng notes: Lecture Notes 1, Part I, Chapters 2, 3, 4; Part II Ch. 5 and Part VI Ch. 1 (Bias-Variance) Note that Part VI is in file cs229-notes4. |
| 3rd/fourth week | Ng's notes: Part II Ch. 7. Review probability (probability theory review section notes 2 from the Stanford 229 class, or All of Statistics chapters 2, 3, 4), and Naive Bayes (Ng part IV ch 2) |
| 4th week | Ng Part IV ch 1 (Gaussian discriminant analysis) |
| 5th week |
Ng Part IV ch 2 (Naive Bayes), Part II ch 6 (Perceptron algorithm) The Mitchell text has a good presentation of Naive Bayes for text processing in section 6.10. |
| Ng Part V, chapters 1-8 (support vector machines) | |
| Decision trees: Chapters in Russel and Norvig, or Mitchell, or wikipedia page | |
|
Neural networks: backpropagation handout. See also convolutional networks tutorials. |
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Clustering and mixture of Gaussians, Ng's Lecture Notes 7(a) and 7(b) |