diochnos/teaching/CS4033-5033/2020F
CS 4033/5033 – Machine Learning (Fall 2020)
The class is cross-listed as CS 4033 and CS 5033, so that both undergraduate and graduate students can enroll simultaneously. No student may earn credit for both 4033 and 5033.
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Course Description
Topics include decision trees, relational learning, neural networks, Bayesian learning, reinforcement learning, multiple-instance learning, feature selection, learning appropriate representations, clustering, and kernel methods. No student may earn credit for both 4033 and 5033.
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Basic Information
Syllabus
The syllabus is available here.
Time and Location
Mondays and Wednesdays, 5:30pm – 6:45pm, Dale Hall 0218.
Contact Information
Please see here.
Teaching Assistants
TBA
Office Hours
I will be holding my office hours at the following times.
- Mondays
- 10:30am – 12:30pm, 244 Devon Energy Hall (Dimitris)
- Wednesdays
- 10:30am – 12:30pm, 244 Devon Energy Hall (Dimitris)
Please note that while anyone is welcome during the entire 2-hour time period that I have reserved on Mondays and Wednesdays, CS 5970 will have precedence during the first hour (10:30am – 11:30am) and CS 4033/5033 will have precedence during the second hour (11:30am – 12:30pm).
Exceptions to the Regular Schedule of Office Hours
If you want to meet me outside of my office hours, please send me an email and arrange an appointment.
Exceptions to the Regular Schedule of Office Hours for the TAs
As exceptions appear along the way, they will also be announced here.
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Important Coronavirus-Related Information
We have the following links.
- Additional Technologies
- Questions and Answers about the Coronavirus
- Instructional Faculty
- Masking Policy Syllabus Statement — Also has a link to a webpage with full details.
- Syllabus Attendance Policy
- COVID-19 Screening and Reporting Tool
- COVID-19 Curbside Testing
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Homework Assignments
Assignment 1: To be announced on Monday, August 31. Due Wednesday, September 9.
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Machine Learning Resources
Books
The two books that we plan to use for the course are available for free in electronic format in the following links:
- Reinforcement Learning: An Introduction, by Richard S. Sutton and Andrew G. Barto.
- The Elements of Statistical Learning, by Trevor Hastie, Robert Tibshirani, and Jerome Friedman.
Another book that I like a lot and recommend to people who are starting with machine learning is the following one:
- Machine Learning, by Tom Mitchell.
Personal Notes
- TBA
Notes by Others
- TBA
Papers
- Machine Learning that Matters, by Kiri L. Wagstaff
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Class Log
A log for the class will be held online here.
Class 1 (Aug 24, 2020)
Discussion on syllabus and policies.
Pretest in class.
Class 2 (Aug 26, 2020)
Assigned Reading: Elements of Statistical Learning (ESL), Chapter 1.
Assigned Reading: Sutton & Barto: Chapters 1 and 2.
Assigned today: Think about short and long projects. Think about the topic for your RL project.
Discussion on projects. Introduction to Machine Learning and Reinforcement Learning.
Class 3 (Aug 31, 2020)
TBA.
Class 4 (Sep 2, 2020)
TBA.
Class 5 (Sep 7, 2020)
TBA.
Class 6 (Sep 9, 2020)
TBA.
Class 7 (Sep 14, 2020)
TBA.
Class 8 (Sep 16, 2020)
TBA.
Class 9 (Sep 21, 2020)
TBA.
Class 10 (Sep 23, 2020)
TBA.
Class 11 (Sep 28, 2020)
TBA.
Class 12 (Sep 30, 2020)
TBA.
Class 13 (Oct 5, 2020)
TBA.
Class 14 (Oct 7, 2020)
TBA.
Class 15 (Oct 12, 2020)
TBA.
Class 16 (Oct 14, 2020)
TBA.
Class 17 (Oct 19, 2020)
TBA.
Class 18 (Oct 21, 2020)
TBA.
Class 19 (Oct 26, 2020)
TBA.
Class 20 (Oct 28, 2020)
TBA.
Class 21 (Nov 2, 2020)
TBA.
Class 22 (Nov 4, 2020)
TBA.
Class 23 (Nov 9, 2020)
TBA.
Class 24 (Nov 11, 2020)
TBA.
Class 25 (Nov 16, 2020)
TBA.
Class 26 (Nov 18, 2020)
TBA.
Class 27 (Nov 23, 2020)
TBA.
Nov 25, 2020
Thanksgiving; no classes.
Class 28 (Nov 30, 2020)
TBA.
Class 29 (Dec 2, 2020)
TBA.
Class 30 (Dec 7, 2020)
TBA.
Class 31 (Dec 9, 2020)
TBA.
Thursday, December 17, 2020 (4:30pm – 6:30pm)
Normally this would be the date and time of the final exam. However, we will not have a final exam as the class has a semester-long project.
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