
In this introductory tutorial, we will explore the complete end-to-end machine learning workflow development process using KNIME Analytics Platform, a visual, low-code data science environment. We will work with a couple of simple datasets, learn how to merge and preprocess them, and then build and compare ML models using a k-fold cross-validation experimental design. We’ll also demonstrate how KNIME visualization nodes help tell the story of your analysis, and make it easy to understand for others. The session will highlight how KNIME makes data ingestion, preparation, model training, evaluation, and comparative analysis both intuitive and efficient—even for beginners.

