Welcome to CMSC 422. Machine Learning studies representations and algorithms that allow machines to improve their performance on a task from experience. This is a broad overview of existing methods for machine learning and an introduction to adaptive systems in general. Emphasis is given to practical aspects of machine learning and data mining.
| Week Starting | Tuesday | Thursday |
|---|---|---|
| 01/26 | Snow Week (No class) | |
| 02/02 | Course Intro
Welcome to Machine Learning
|
Decision Trees Reading: Chapter 1 of the text book |
| 02/09 | Decision Trees Contd. / Ensemble learning |
K-Nearest Neighbors Reading: Chapter 3 of the text book |
| 02/16 | Perceptron Reading: Chapter 4 of the text book Convex Review |
Convergence Analysis of Perceptron Reading: Chapter 4 of the text book Convex Review |
| 02/23 | Linear Classifiers
Reading: Chapter 7 of the text book |
Gradient Descent |
| 03/02 | Naive Bayes' Classifier Reading: Chapter 9 of the text book |
Naive Bayes' Classifier, Logistic Regression Reading: Part II of notes |
Instructor: Mohammad Nayeem Teli (nayeem at cs.umd.edu)
Office: IRB 2224
Office Hours: M 2 - 3 PM
| Name | Email (at umd.edu) |
|---|---|
| Kiarash Banihashem | kiarash |
| Soumya Ghosal | sghosal |
| Michael-Andrei Panaitescu-Liess | mpanaite |
| Roksana Khanom | rkhanom |
| Chi-Chang Lee | changlee |
| Haiyang Ying | yinghy |
| Georgios Milis | milis |
| Monday | Kiarish: 10:00 AM - 11:00 AM, Roksana: 11:00 AM - 3:00 PM, Kiarish: 1:00 - 2:00 PM |
| Tuesday | Chi-Chang: 1:00 - 3:00 PM George: 3:00 - 5:00 PM (IRB 3230 ) |
| Wednesday |
George: 9:00 - 11:00 AM (IRB 3230) Kiarish : 11:00 AM - 1:00 PM Haiyang: 1:00 - 5:00 PM |
| Thursday |
Soumya: 1:00 PM - 5:00 PM Chi-Chang: 1:00 - 3:00 PM |
| Friday |
Michael: 11:00 AM - 3:00 PM, |
Please note that a TA may need to leave 5 minutes before the end of the hour in order to go to his/her class. Please be understanding of their schedules.
| Homework | Due Date* |
|---|