CS 181
General
Syllabus
Calendar
Staff
Office Hours
Resources
Beyond CS 181
Schedule
Lecture Recaps
Lecture 1 (Welcome to CS181)
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 12 (Support Vector Machines II)
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)
Lecture 23 (Final Lecture)
Sections
HW
Beyond CS 181