Applied Data Mining (UN3106) • Spring 2018

This class is an introduction to basic principles of machine learning. We will focus on so-called supervised learning problems, where example data is available from which an algorithm can learn before it is applied to solve a problem.

Prerequisites: STAT UN2103. Some homework problems will involve programming. Familiarity with R is assumed.

Class specs

Time: Tue/Thu 2:40pm-3:55pm
Room: 627 Mudd
Teaching Assistant: Phyllis Wan
TA office hours: Tue 4-6pm, Wed 3:30-4:30pm
Instructor office hours: Tue 9-10am
Midterm exam: 8 March.
The final exam will be scheduled by the school.
Grading: 40% homework + 30% midterm exam + 30% final exam

Homework

[ 1 ]   [ 2 ]   [ 3 ]   [ 4 ]   [ 5 ]   [Digit data]   [WDBC data]

Material

Course Slides

Here is the complete set of course slides as a single file.

No textbook is required. The relevant material are the slides.