Regression in Machine Learning
This workshop will take place on Wednesday, 22nd April 9:30-1:30pm AEST.
Regression is a fundamental technique in supervised machine learning which is used to predict continuous outcomes based on input data. In this interactive 4-hour workshop, participants will explore the core concepts of regression, including simple and multiple linear regression, regularisation techniques (Ridge & Lasso), model evaluation and touch on Bayesian methods and uncertainty quantification. Through hands-on coding exercises in Python (Scikit-Learn, statsmodels, cmdstanpy, NumPy, Pandas, Matplotlib), attendees will learn how to build, interpret, and optimise regression models using real-world datasets. By the end of the session, participants will have the practical skills to apply regression techniques to solve predictive modelling problems effectively. No prior machine learning experience is required, however basic Python and statistics knowledge is required.
