Supervised learning in Autonomous Systems

Catalog description

Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs. Using probabilistic programming languages, this course will illustrate supervised machine learning concepts via data preparation, training data, model evaluation, and operationalization. Common machine learning algorithms for supervised learning such as K-nearest neighbors, logistic regression, decision trees and random forests will be explored and operationalized within an autonomous system.