Craft Effective Machine Learning Pipelines
From Hand-Design To Automatic Methods
In this session, you'll learn about
- How to clean and prep your data like a pro: From handling missing values to managing imbalanced datasets.
- The secrets of feature engineering: Transformations, feature selection, and dimensionality reduction that make your models shine.
- Model training and tuning hacks: Hyperparameter optimization, cross-validation strategies, and ensuring reproducibility.
- Pipeline design that scales: Learn to structure pipelines for modularity, maintainability, and future-proofing.
- Deployment done right: Integrating pipelines into production and monitoring for drift and performance.
6 MB
Dr. Leonardo Trujillo
Professor and leading researcher at the Tecnológico Nacional de México-Instituto Tecnológico de Tijuana (ITT).
He holds a Ph.D. in Computer Science from CICESE and specializes in evolutionary computation, genetic programming, machine learning, and AI. Dr. Trujillo has led national and international research projects and published widely in top journals and conferences. He currently serves as Editor-in-Chief of Genetic Programming and Evolvable Machines (Springer) and Co-Chair of the NEO Workshop Series.
