For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/ai
Associate Professor Percy Liang
Associate Professor of Computer Science and Statistics (courtesy)
https://profiles.stanford.edu/percy-liang
Assistant Professor Dorsa Sadigh
Assistant Professor in the Computer Science Department & Electrical Engineering Department
https://profiles.stanford.edu/dorsa-sadigh
To follow along with the course schedule and syllabus, visit:
https://stanford-cs221.github.io/autumn2021/#schedule
0:00 Introduction
0:06 Machine learning: linear classification
0:14 Linear classification framework
2:43 An example linear classifier
6:26 Hypothesis class: which classifiers?
7:34 Loss function: how good is a classifier?
10:07 Score and margin
11:55 Zero-one loss rewritten
12:43 Optimization algorithm: how to compute best?
16:28 Digression: logistic regression
17:28 Gradient of the hinge loss
19:34 Hinge loss on training data
22:34 Gradient descent (hinge loss) in Python
26:16 Summary so far