STATS214 / CS229M: Machine Learning Theory

Administrative information
Time/location:
Instructor: Tengyu Ma
Course assistants:
Contact: Please use Piazza for all questions and discussions.
Course content
Description: When do machine learning algorithms work and why? How do we formalize what it means for an algorithm to learn from data? How do we use mathematical thinking to design better machine learning methods? This course focuses on developing a theoretical understanding of the statistical properties of learning algorithms.
Topics:
Logistics and FAQ

Please see this doc for all the logistic information and some frequently asked questions.
Scribed notes

You can find all tex and pdf files for scribed notes in this github repo. You can also click on lectures in the following shcedule to view each individual scribe note.
Schedule
Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8
  • Mon 03/01:
  • Wed 03/03
Week 9
  • Mon 03/08:
  • Wed 03/10:
  • Wed 03/10: Homework 3 due
Week 10
  • Mon 03/15:
  • Wed 03/17:
  • Fri 03/19: Paper review due
Texts and References

There is no required text for the course. A number of useful references: