CS229: Machine Learning


Tengyu Ma
Chris RĂ©

Course Description   This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs, practical advice); reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.

Course Information

Time and Location
Monday, Wednesday 3:15 PM - 4:45 PM (PST) in NVIDIA Auditorium
Quick Links
(You may need to log in with your Stanford email.)
Contact and Communication
Due to a large number of inquiries, we encourage you to first read the Course Logistics and FAQ quick link for commonly asked questions, and then create a post on Ed to contact the course staff. Please do NOT reach out to the instructors directly, otherwise your questions may get lost.
This quarter we will be using Ed as the course forum.
  • All official announcements and communication will happen over Ed.
  • Any questions regarding course content and course organization should be posted on Ed. You are strongly encouraged to answer other students' questions when you know the answer.
  • If there are private matters specific to you (e.g special accommodations, requesting alternative arrangements etc.), please create a private post on Ed.
  • For longer discussions with TAs, please attend office hours.
  • TA office hours can be found on Canvas. For the course calendar, see also Canvas and the Syllabus and Course Materials quick link.
  • Before the beginning of the course, please contact the course coordinator for logistical questions (ideally after consulting the FAQ link).

Course Staff

Course Coordinator
Amelie Byun
Head Course Assistant
Masha Itkina
Course Assistants
Kamil Ali
Nandita Bhaskhar
Yining Chen
Kefan Dong
Xinru (Lucy) Hua
Shubham Anand Jain
Ananya Kumar
Kevin Li
Ziang Liu
Christopher Frederic Wolff
Sang Michael Xie
Honglin Yuan