COMP-3705Unsupervised Machine Learning
Unsupervised machine learning is a subfield of machine learning where models are trained to identify clusters and find relationships in unlabelled data. This course builds upon concepts from previous courses to describe how unsupervised learning algorithms work, as well as how they are constructed and coded. Students will use Python to develop the code for clustering models, Autoencoders and topic models; real data will be used to train, validate and test these models for common use cases in business and data science.
