Skip over navigation

Course Offerings

Course Evaluation Results

Course Details

Spring 2018-2019
* COS 324   Graded A-F, P/D/F, Audit

Introduction to Machine Learning

Ryan P. Adams

Provides a broad introduction to different machine learning paradigms and algorithms, providing a foundation for further study or independent work in machine learning, artificial intelligence, and data science. Topics include linear models for classification and regression, support vector machines, neural networks, clustering, principal components analysis, Markov decision processed, planning, and reinforcement learning.


Sample reading list:
See instructor for complete list

Reading/Writing assignments:
Problem sets and programming exercises. Programming assignments will use python.

Requirements/Grading:
Mid Term Exam - 20%
Final Exam - 20%
Problem set(s) - 60%

Prerequisites and Restrictions:
MAT 201 or 203; MAT 202 or 204; COS 226; ORF 245, ORF 309 or MAT 385 or permission of instructor.

Other information:
This is recommended as the first course in machine learning for COS majors.

Website:  http://www.cs.princeton.edu/courses/archive/spring2019/cos324

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
40095 L01 01:30:00 pm - 02:50:00 pm M W   Computer Science Building   104   Enrolled:51 Limit:75
40096 P01 07:30:00 pm - 08:20:00 pm W        Enrolled:22 Limit:25
40097 P02 01:30:00 pm - 02:20:00 pm F        Enrolled:25 Limit:25 Closed
40098 P03 02:30:00 pm - 03:20:00 pm F        Enrolled:4 Limit:25