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!

Les enseignants sont invités à télécharger les diapositives https://www.slideshare.net/RebeccaBilbro/learning-machine-learning-with-yellowbrick via SlideShare sous la forme d’une présentation PowerPoint, et à les ajouter à leur matériel de cours pour les aider à enseigner ces concepts importants.

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