CS 181
General
Syllabus
Calendar
Staff
Office Hours
Resources
Schedule
Lecture Recaps
Lecture 1 (Nonparametric Regression)
Lecture 2 (Linear Regression)
Lecture 3 (Probabilistic Linear Regression)
Lecture 4 (Linear Classification)
Lecture 5 (Probabilistic Classification)
Lecture 6 (Model Specification)
Lecture 7 (Bayesian Model Specification)
Lecture 8 (Neural Networks I)
Lecture 9 (Neural Networks II)
Lecture 10 (Support Vector Machines I)
Lecture 11 (Support Vector Machines II)
Lecture 12 (EthiCS)
Lecture 13 (Clustering)
Lecture 14 (Mixture Models)
Lecture 15 (PCA)
Lecture 16 (Topic Models)
Lecture 17 (Graphical Models)
Lecture 18 (Inference in Bayes Nets)
Lecture 19 (Hidden Markov Models)
Lecture 20 (Markov Decision Processes)
Lecture 21 (Reinforcement Learning I)
Lecture 22 (Reinforcement Learning II)
Sections
HW
Course Staff
People
Instructors
Finale Doshi-Velez
David Parkes
Teaching Fellows
Nari Johnson
(Head TF)
Mark Goldstein
(Head TF)
Andrew Kim
Bill Zhang
(Beyond CS 181)
Dylan Li
Ife Omidiran
Jonathan Chu
Karthik Rao
Katherine Tian
Lucy Liu
Prasidh Chhabria
Richard Muratore
Rylan Schaeffer
Sanjana Narayanan
Yash Nair
Contacting us
When contacting staff, Ed is preferred. Please use email sparingly.