ECS 171 Machine Learning (Winter 2018)
Winter 2018


Mon/Wed 6:10 pm - 7:30 pm




Instructor: Cho-Jui Hsieh
Office location: Mathematical Sciences Building (MSB) 4232
Email: chohsieh@ucdavis.edu
Office hours: TBD
TA: Pei-Hung (Patrick) Chen (phpchen@ucdavis.edu), Xuanqing Liu (xqliu@ucdavis.edu)
TA office hours: Thursday 10am-11am (Kemper 55)



Announcements

Overview

Course description

This course will roughly follow Learning from Data, which covers several important foundamental machine learning concepts and algorithms. Then we will introduce supervised learning algorithms (deep neural networks, boosting tress, SVM, nearest neighbors) and unsupservised learning algorithms (clustering, dimension reduction).



Schedule

Date
Topic
Readings and links
Lectures
Assignments
Mon 1/8
Overview. The Learning Problem.

LFD 1.1, 1.2

lecture_1


Wed 1/10
Feasibility of Learning

LFD 1.3, 3.1

lecture_2


Wed 1/18
Linear Models I

LFD 3.2, 3.3

lecture_3


Mon 1/22
SGD, Non-linear transforms

SGD and LFD 3.4




Wed 1/24
Training versus testing

LFD 2.0, 2.1




Mon 1/29
Theory of generalization

LFD 2.1