COMP-2704Supervised Machine Learning
Supervised machine learning is a subfield of machine learning where algorithms are trained on labelled data to classify items or predict outcomes. This course builds upon concepts to describe how supervised learning algorithms are constructed and coded. Students will use Python to develop the code for supervised learning algorithms including polynomial regression, support vector machines and decision trees; data will be used to train, validate and test these models for common use cases in business and data science.