Predictive Analytics and Machine Learning Module 2: Predictive Modelling for Categorical Data (Synchronous e-Learning)

Building on a previous module on predictive models with numerical outcome data, the module will further improve participants’ understanding of classification problems (predicting categorial outcomes) in supervised machine learning, executing and interpreting predictive models with Random Forest algorithm and XG Boost (a decision-tree-based ensemble Machine Learning algorithm that uses a gradient boosting framework).

Participants will learn the differences between solving regression and classification problems in the workflow of predictive models (e.g., performance metrics). They will be shown how to run and draw insights from both binary classification and multi-class (multinomial) classification tasks.

Add to Comparison Back to All Courses