CS X459.35 - Supervised Machine Learning: Introduction to Classification Algorithms with Python

Course Description

Explore popular classification methods such as kNN, logistic regression, decision trees, and random forests. Building on linear regression covered in the previous course, you learn when to use each algorithm in a real business setting. You will also evaluate classification algorithms by using confusion matrices, ROC curves, and understanding the measure (area under the curve -AUC), and how to use ensemble methods, which are the most efficient when building large- scale models.

Prerequisites

CS X459.34 - Supervised Machine Learning: Regression and Time Series Analysis with Python (Pass)