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Want to see how real machine learning gets built and deployed using real-world data? In this hands-on session, Ethan Pirso from Compass Analytics walks through how to use Dataiku to build and monitor ML models — using examples from the pharmaceutical industry. From forecasting sales to understanding patient behavior, you’ll learn how teams can clean data, train models, and track performance in one easy-to-use platform — with or without code. Whether you’re new to machine learning or looking for a better way to manage your workflows, this demo will show you how it all fits together. What You'll Learn: How to use Dataiku’s Visual ML tools to build ML projects step-by-step Forecasting future pharma sales using time series modeling Identifying unusual patient behavior with clustering Predicting treatment adherence with regression models How to track and respond to model performance changes over time How explainability and drift detection work in production Timestamps: 00:34 Introduction 01:55 What Will Be Covered in the Video 02:34 What is Dataiku 04:38 Pharma Landscape Today 06:54 What is Machine Learning 11:50 Machine Learning in Dataiku 15:45 Hands on Project 01:00:25 Q&A Want to learn more about Dataiku and how to get more from your data? Visit: https://compassdata.ca