An introductory session exploring the core principles of how machine learning systems learn from data, make predictions, and form the foundation of modern AI.

Join us for an in-depth introduction to the foundations of modern machine learning. This session will focus on how learning algorithms use data to recognize patterns, make predictions, and support real-world applications. We will concentrate on supervised learning, providing clear explanations of core models such as linear and logistic regression, decision trees, random forests, support vector machines, and basic neural networks. The session is designed to give participants a strong conceptual starting point before progressing to more advanced AI topics. To help you get the most out of the discussion, we encourage you to review the Google ML Crash Course prior to attending.