Supervised Learning: Classification

Supervised Learning: Classification

IBM NIC-IB-W7103G

EUR 364.38
excl. VAT

This course introduces you to one of the main types of modeling families of supervised Machine Learning: Classification. You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. The hands-on section of this course focuses on using best practices for classification, including train and test splits, and handling data sets with unbalanced classes.

Who should attend

This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Classification techniques in a business setting.

Course Prerequisites

To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics.

Additional information

PLEASE NOTE: It may take 2-3 business days for your course access to be activated. You will receive an email from us with all necessary details.

Write Your Own Review

Only registered users can write reviews. Please Sign in or create an account