Machine Learning Interpretable: interpretML y LIME

This practical and effective course provides in-depth training on generating interpretable Machine Learning models using techniques such as interpretML and LIME. You will gain a comprehensive understanding of model interpretability fundamentals and how to apply libraries for interpretability, including LIME and interpretML.

• Learn the fundamentals of model interpretability.
• Apply libraries for model interpretability such as LIME and interpretML.
• Develop interpretable models of Random Forest and Explainable Boosting Machine.

By the end of this course, you will be equipped to train Glassbox models and comprehend the rationale behind their decisions, enabling a deeper understanding of predictions and enhancing the transparency of your models.