You can download the syllabus here. The syllabus includes information on grading, course goals, and policies I will use in teaching this course.
We will be using Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow by Aurélien Géron. This is more of a reference book than a traditional textbook, that you will be able to use after you have graduated.
There will be five homework assignments over the course of the semester. They will be large—please allot them plenty of time. General specifications for your work can be found here.
This is a tentative schedule for the class. I may change it depending on how the class progresses.
Week | Dates | Readings | Homework | Files | Due Date | |||
---|---|---|---|---|---|---|---|---|
1 | Jan. 16 - 19 | Python Tutorial “Humans Need Not Apply” |
— | — | — | |||
2 | Jan. 22 - 26 | — | — | — | — | |||
3 | Jan. 29 - Feb. 2 | — | Sliding Puzzle | slidingpuzzle.py easy.puz square.puz impossible.puz | Feb. 11 | |||
4 | Feb. 5 - 9 | — | — | — | — | |||
5 | Feb. 12 - 16 | “The Man vs. The Machine” | — | — | — | |||
6 | Feb. 19 - 23 | Chapters 1 - 3 Chess’s New Best Player... “The Evolution of Trust” |
Connect Four | connect4.py connect4player.py | Feb. 25 | |||
7 | Feb. 26 - March 1 | Chapter 6 | ||||||
8 | March 4 - 8 | Chapter 10 “How Machines Learn” |
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Midterm: Week 8 | ||||||||
Spring Break! | ||||||||
9 | March 18 - 22 | Chapter 11 | Decision Trees | voting-data.tsv | March 24 | |||
10 | March 25 - 29 | — | ||||||
11 | April 1 - 5 | Chapter 14 | ||||||
12 | April 8 - 12 | Google Blog: Inceptionism... | Convolutional Neural Networks | (see class-only page) | April 7 | |||
13 | April 15 - 19 | Chapter 9 | ||||||
14 | April 22 - 24 | — | k-Means | — | April 28 | |||
Final Exam: Friday, May 12, 4:00 |
Projects are due at the end of class. Click here for some ideas.
Click here if you’re in the class, for more useful information.
Any other useful resources will be put here.