Machine Learning

Catalog description

This is an introductory course in machine learning. The course focuses on understanding the basic operations and applications in the field. Topics include data acquisition, classification, regression, model fitting, supervised and unsupervised training, k-means clustering, optimization training, random forests, recommender systems, sentiment analysis, and visualizations.