Yellowbrick for Teachers
For teachers and students of machine learning, Yellowbrick can be used as a framework for teaching and understanding a large variety of algorithms and methods. In fact, Yellowbrick grew out of teaching data science courses at Georgetown’s School of Continuing Studies!
The following slide deck presents an approach to teaching students about the machine learning workflow (the model selection triple), including:
feature analysis
feature importances
feature engineering
algorithm selection
model evaluation for classification and regression
cross-validation
hyperparameter tuning
the scikit-learn API
Teachers are welcome to download the slides via SlideShare as a PowerPoint deck, and to add them to their course materials to assist in teaching these important concepts.