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Home | CS 189/289A
CS 189/289A (Introduction to Machine Learning) covers: Theoretical foundations, algorithms, methodologies, and applications for machine learning. Topics may include supervised methods for regression a...
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Syllabus | CS 189/289A
Syllabus
Introduction
Course Overview
The homepage has a week-by-week coverage on the topics covered in this course. Note, this course is focused on teaching the basics of machine learning and a ...
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Resources | CS 189/289A
Tips
These tips have been collected through the years from professors, past and present. You can also check out the Learning How To Learn Coursera course for other general tips.
Don’t fall behind
I...
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Past Exams | CS 189/289A
Past Exams
Below are past exams from different iterations of the course. Note that the fall iterations tend to be similar to each other, and the spring iterations tend to be similar to each other. Th...
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Calendar | CS 189/289A
Calendar
Below are the timings for lectures, office hours, homework party, and discussion sections. This page will be updated periodically as times change.
Lectures
Dwinelle 155 on
Tuesdays and Th...
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CS 189
Homeworks
All homeworks are partially graded and it is highly-recommended that you do them. Your lowest homework score will be dropped, but this drop should be reserved for emergencies. Here is the se...