Supervised Machine Learning: Random Forests

This workshop will introduce participants to Supervised Machine Learning (SML) and Random Forests (RFs) using Python’s Scikit-learn library. We’ll start with a brief explanation of Anaconda and the Jupyter notebook environment (although not required for the participant, the instructor will be using these tools). We’ll then introduce fundamental concepts related to both SMLs and RFs, but the main focus of the workshop will be on using Python and Scikit-learn RFs to solve SMLs problems. Accordingly, we’ll use a couple of example datasets to demonstrate how to create, apply and test RF models using Scikit-learn. Although not required, we recommend all participants to have a basic knowledge of Python.