BAIT509

BAIT509 - Business Applications of Machine Learning

BAIT509 - Business Applications of Machine Learning

This is the home page for the 2019 iteration of the course BAIT 509 at the University of British Columbia, Vancouver, Canada. The core syllabus can be found at sauder_syllabus.pdf, but anything listed on this website will take precedence.

This repository is avaiable as a website.

Learning Objectives

By the end of the course, students are expected to be able to:

Teaching Team

At your service!

Name Position GitHub Handle
Tomas Beuzen Instructor @tbeuzen
  TA  
  TA  
  TA  

Class Meetings

Details about class meetings will appear here as they become available. Readings are optional, but should be useful.

# Topic Recommended Readings
1 Intro to the course, tools, and ML ISLR Section 2.1
2 Irreducible and Reducible Error ISLR Section 2.2 (you can stop in 2.2.3 once you get to the “The Bayes Classifier” subsection).
3 Local methods ISLR’s “K-Nearest Neighbors” section (in Section 2.2.3) on page 39; and Section 7.6 (“Local Regression”).
4 Model Selection ISLR Section 5.1; we’ll be touching on 6.1, 6.2, and 6.3 from ISLR, but only briefly.
5 Classification and Regression Trees ISLR Section 8.1
6 Refining business questions This blog post by datapine does a good job motivating the problem of asking good questions. This blog post by altexsoft does a good job outlining the use of supervised learning in business.
7 Ensembles ISLR Section 8.2
8 Beyond the mean and mode  
9 SVM Section 9.1, 9.2, 9.4 in ISLR. The details aren’t all that important. 9.3 is quite advanced, but I’ll be discussing the main idea behind it in class.
10 SVM continuation; wrapup; alternatives to accuracy Alternative measures, and ROC

Assessments

Links to assessments will be made available when they are ready. The deadlines listed here are the official ones, and take precendence over the ones listed in the sauder syllabus.

Assessment Due Weight
Participation January XX at 18:00 10%
Assignment 1 January XX at 18:00 20%
Assignment 2 January XX at 18:00 20%
Assignment 3 February XX at 18:00 20%
Final Project February XX at 23:59 30%

Please submit everything to UBC Canvas.

Office Hours

Want to talk about the course outside of lecture? Let’s talk during these dedicated times.

Teaching Member When Where
Tomas Beuzen Tuesdays 13:00-14:00 ESB 1045
     
     
     
     
     

Additional Resources