Courses

ITS 520 - Applied Machine Learning

This course will cover the fundamental concepts related to machine learning. Topics include:

Prerequisites: Programming skills up to data structures and a senior/graduate level course in statistics. Knowledge of Python and Linux.

Time Place

Monday 2-5 pm on Zoom. Zoom Meeting Room ID and code on Brightspace
 

Textbook

Python Machine Learning by Sebastian Raschka

Instructor

Ricardo A. Calix, Ph.D.
Purdue University Northwest
rcalix@pnw.edu

Office Hours

My office is at 241 Anderson

On-Line Office Hours

Thursday 2-4 pm (or by appointment) on Zoom. Zoom Meeting Room ID and code on Blackboard

About Purdue University Northwest

Code

GitHub
 

Videos

Brightspace (Submit homework on Brightspace)

Brightspace

Datasets

Lab Environment

Environment:

AWS

WL Scholar

Course Materials

Labs

  1. More materials on Brightspace

Tools

We will use the following software:

  1. Linux
  2. Python
  3. Anaconda

Calendar Fall 2020 (Subject to change)

Mon Tue Wed Thu Fri

Aug 24

Intro to the course 

video

Aug 25

 

Aug 26

Machine Learning motivation

video

Aug 27

 
Aug 28

Aug 31

Basics of machine learning

video

Sep 1
 

Sep 2

Weka

video

Sep 3
 
Sep 4
Sep 7 Sep 8
 
Sep 9 Sep 10
 
Sep 11

Sep 14

ML performance metrics

video

Sep 15
 

Sep 16

WL GPU Scholar

Anaconda

video

Sep 17
 
Sep 18
Sep 21 Sep 22
 
Sep 23

 
Sep 24
 
Sep 25

 
Sep 28 Sep 29
 
Sep 30 Oct 1
 
Oct 2
Oct 5

 
Oct 6
 
Oct 7

 
Oct 8
 
Oct 9

 
Oct 12

 
Oct 13
 
Oct 14

 
Oct 15
 
Oct 16
 
Oct 19

 
Oct 20

 
Oct 21

 
Oct 22

 
Oct 23

 
Oct 26

 
Oct 27

 
Oct 28

 
Oct 29

 
Oct 30

 
Nov 2

 
Nov 3

 
Nov 4

 
Nov 5

 
Nov 6
 
Nov 9 Nov 10
 
Nov 11 Nov 12
 
Nov  13
Nov 16 Nov 17
 
Nov 18 Nov 19
 
Nov 20
 
Nov 23 Nov 24
 
Nov 25 Nov 26
 
Nov 27
Nov 30
 
Dec 1
 
Dec 2
 
Dec 3
 
Dec 4
 
Dec 7 Dec 8
 
Dec 9
 
Dec 10
 
Dec 11
 
Dec 14
Finals
Dec 15
Finals
Dec 16
Finals
Dec 17
Finals
Dec 18
Finals