STAT 486
Machine Learning
Statistics
College of Physical and Mathematical Sciences
Course Description
Supervised and unsupervised learning; model evaluation; recommendation systems; natural language process and unstructured data; deep learning.\n
When Taught
Fall and Winter
Grade Rule
Grade Rule 8: A, B, C, D, E, I (Standard grade rule)
Min
3
Fixed
3
Fixed
3
Fixed
0
Title
Machine learning categories
Learning Outcome
Differentiate between categories of machine learning problems
Title
Using data
Learning Outcome
Use data to answer interesting and complex research questions
Title
Understanding pitfalls
Learning Outcome
Understand common machine learning pitfalls and demonstrate how to avoid or correct for them
Title
ML algorithms
Learning Outcome
Implement and interpret machine learning algorithms in common data science software
Title
Identify ML for various data types
Learning Outcome
Identify the machine learning algorithm(s) that is(are) most relevant for various data types and research questions
Title
Communication
Learning Outcome
Communicate machine learning algorithms and results in a variety of context, including informal and formal reports and presentations
