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