CS229T/STATS231: Statistical Learning Theory

Administrative information
Instructor: Percy Liang (office hours: Tue 4-5pm, Thu 11am-12pm in Gates 250)
Course assistants:
Contact: Please use Piazza for questions and discussions.
Course content
Description: When do machine learning algorithms work and why? This course focuses on developing a theoretical understanding of the statistical properties of learning algorithms.

To submit electronically, open up a terminal, (i) copy your submission file(s) (e.g., hw0.pdf) to cardinal.stanford.edu:

        scp <your submission file(s)> <your SUNetID>@cardinal.stanford.edu:
and (ii) run the submit script:
      ssh <your SUNetID>cardinal.stanford.edu python /usr/class/cs229t/WWW/submit.py <hw0|hw1|hw2|hw3|p1|p2|p3> .
You can submit multiple times; each submission will just replace the previous one.

By default, no late work is accepted. Under extentuating circumstances, you may request an extension by contacting the course staff.
Collaboration policy: we encourage you to form study groups and discuss homeworks. However, you must write up all homeworks and code from scratch independently without referring to any notes from the joint session. Please follow the honor code.

Schedule (subject to change)
Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10