MSCI 446 - Introduction to Machine Learning

MSCI 446 - Introduction to Machine Learning is a popular technical elective that management engineering students typically take in third or fourth year. Data mining is about finding patterns in data, and interpreting those patterns into useful information that can be used to improve decision making. At the end of the course, students are able to:

  • explain how data mining algorithms work
  • apply data mining algorithm to solve real(istic) problems

Student projects in MSCI 446

Students apply what they learn in the course through a significant project which they complete in teams. Students teams are encouraged to be independent and creative in their approach and are expected to choose their own project topic and goals.

What makes subreddits popular?

For example, management engineering students Stylianos Kapadoukakis, Pia Medina, Melissa Pulenzas, and Quinn Turner wanted to understand what makes a meme in subreddits popular. The team collected as many meme posts as possible by using a computer program (programmed in Python) to scrape a number of subreddits and collected a wide variety of explanatory variables including features such as post title, post score, user, and the number of comments. The team also used Google’s Vision Application Programming Interface (API) to mine the meme’s embedded text and colour distributions. Their analysis interpreted how the features mentioned above impacted a meme’s popularity.


A graph produced by the analysis of the student team

A graph produced by the analysis of the student team