The course will cover major topics in machine learning with applications to animal biosciences and related areas. This is a project-based course and it will have a computational component and a lab component focused on Python programming.
The topics include: data types, problem types (e.g. classification, regression, clustering, dimensionality reduction), models (e.g. decision trees, artificial neural networks, k-nearest neighbour, k-means), quality measures (e.g. accuracy, precision, recall, errors, correlations), data (re)sampling procedures (e.g. k-fold cross validation, fixed percentage splits), Python implementations using various libraries (e.g. pandas, scipy, numpy, scikit-learn).
Credit Weight: 0.50
Semester Offering: Winter, Summer
Learn More: https://animalbiosciences.uoguelph.ca