This is an introductory class in the field of machine learning. Throughout the course, students will delve into the basic principles of machine learning. By the end of the course, students will 1) understand the foundation, classic techniques, applications, and challenges of machine learning; 2) be able to apply basic machine learning algorithms to solve real-world problems.
- Instructor:
- Prof. Shiyu Chang, Monday after the lecture
- TAs:
- Qiucheng Wu: Thursday 6-7pm @ Phelps 3530
- Gyuwan Kim: Tuesday 6:30-7:30pm @ Trailer 936
- Alvin Liu: Tuesday 7:30-8:30pm @ Trailer 936
- ULAs:
- Tanay Biradar: Thursday 12-1pm @ Trailer 936
- Reader:
- Wanjing Huang: Thursday 6-7pm @ Phelps 3530
The course piazza can be accessed here. Please note that the main purpose of this discussion forum is for students to exchange ideas and discuss any unclear concepts. TAs are not responsible for answering student questions 24/7.
- Lectures will occur Monday/Wednesday from 5:00-6:15 pm Pacific Time at Chemistry Building 1171.
- Discussion sections will occur on Friday. There are two sections, 4-5 pm and 5-6 pm.
Updated lecture slides will be posted here shortly before each lecture.
| Date | Description | Course Materials | Assignments & Events |
|---|---|---|---|
| Mon, 01/08 | Introduction | [Slides] | [Assignment 0] is out, due on Mon, 01/15 |
| Wed, 01/10 | Review: Linear Algebra | [Slides] | |
| Mon, 01/15 | No class (MLK Jr. Day) | ||
| Wed, 01/17 | Linear Algebra Cont. | [Annotated] | [Assignment 1] is out, due on Fri, 02/02 |
| Mon, 01/22 | Perceptron | [Slides] | |
| Wed, 01/24 | No class | ||
| Mon, 01/29 | Perceptron Cont. | [Annotated] | |
| Wed, 01/31 | Review: Probability | [Slides] [Annotated] | [Assignment 2] is out, due on Mon, 02/19 |
| Mon, 02/05 | Linear Regression | [Slides] | |
| Wed, 02/07 | Linear Regression Cont. | [Annotated] | |
| Mon, 02/12 | Optimization | [Slides] [Annotated] | |
| Wed, 02/14 | Logistic Regression | [Slides] | [Assignment 3] is out, due on Fri, 03/01 |
| Mon, 02/19 | No class (Presidents' Day) | ||
| Wed, 02/21 | Logistic Regression and Midterm Review | [Annotated] [Review] | |
| Mon, 02/26 | Midterm (in class) | ||
| Wed, 02/28 | Naive Bayesian | [Slides] [Annotated] | |
| Fri, 03/01 | Discussion: Non-lienar Transformation | [Slides] | |
| Mon, 03/04 | Decision Tree | [Slides] [Annotated] | [Assignment 4] is out, due on Sun, 03/17 |
| Wed, 03/06 | SVM | [Slides] | |
| Mon, 03/11 | SVM Cont. | [Annotated] | |
| Wed, 03/13 | PCA | [Slides] [Annotated] | |
| Fri, 03/15 | Final Review | [Slides] |
The preparation of this course has benefited from the CSE404 (taught by Dr. Jiayu Zhou) at Michigan State University, and other online materials.