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 |
|---|---|---|
| 08/28 | Course Intro
Welcome to Machine Learning
|
Decision Trees Reading: Chapter 1 of the text book |
| 09/04 | Ensemble learning |
K-Nearest Neighbors Reading: Chapter 3 of the text book |
| 09/11 | K-NN wrap up / Perceptron |
Convergence Analysis of Perceptron Reading: Chapter 4 of the text book Convex Review |
| 09/18 | Linear Classifiers, Gradient Descent and Hinge Loss
Reading: Chapter 7 of the text book |
Gradient Descent Part II |
Instructor: Mohammad Nayeem Teli (nayeem at cs.umd.edu)
Office: IRB 2224
Office Hours:
| Name | Email (at umd.edu) |
|---|---|
| Yijun Liang | yliang17 |
| Isabelle Armene Rathbun | irathbun |
| Yan Wen | ywen1 |
| Wenshan Wu | wwu009 |
| Monday | Yijun: 9:00 - 11:00 AM, Wenshan: 1:00 - 3:00 PM |
| Tuesday | Yijun: 9:00 - 11:00 AM, Isabelle: 4:00 - 5:00 PM |
| Wednesday |
Yan: 10:00 AM - 12:00 PM Isabelle: 3:00 - 5:00 PM |
| Thursday |
Wenshan: 12:15 - 2:15 PM Isabelle: 4:00 - 5:00 PM |
| Friday | Yan: 10:00 - 12:00 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.