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 |
|---|---|---|
| 01/27 | Course Intro
Welcome to Machine Learning
|
Decision Trees Reading: Chapter 1 of the text book |
| 02/03 | Decision Trees Contd. / Ensemble learning |
K-Nearest Neighbors Reading: Chapter 3 of the text book |
| 02/10 | Perceptron Reading: Chapter 4 of the text book Convex Review |
Convergence Analysis of Perceptron Reading: Chapter 4 of the text book Convex Review |
| 02/17 | Convergence Proof Linear Classifiers and loss functions Reading: Chapter 7 of the text book |
Gradient Descent
Reading: Chapter 7 of the text book |
| 02/24 | Naive Bayes Classifier Reading: Chapter 9 of the text book |
Logistic Regression Reading: Part II of notes |
| 03/03 | Logistic Regression Contd. | Binary to Multi-label Classification (OVR & AVA) |
| 03/10 | Multi-class (softmax) | Midterm (03/13) |
| 03/17 | Thanksgiving Break | |
Instructor: Mohammad Nayeem Teli (nayeem at cs.umd.edu)
Office: IRB 2224
Office Hours: Th 3 - 4 PM
| Name | Email (at umd.edu) |
|---|---|
| Pankayaraj Pathmanathan | pan |
| Georgios Milis | milis |
| Michael-Andrei Panaitescu-Liess | mpanaite |
| Kazem Faghih | mkfaghih |
| Osvaldo Luamba Quinjica | quinjica |
| Monday | Osvaldo: 11:00 AM - 1:00 PM, Kazem: 1:00 PM - 3:00 PM, Georgios: 3:00 - 5:00 PM |
| Wednesday |
Kazem : 1:00 - 3:00 PM Georgios: 3:00 - 5:00 PM |
| Thursday |
Michael: 3:30 PM - 5:30 PM |
| Friday |
Osvaldo: 11:00 AM - 1:00 PM, Pankayaraj: 1:00 - 3:00 |
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* |
|---|