Model Interpretability

I covered below topics in my presentation:

  • What is Model Interpretability?
  • Why do we need to build interpretable models?
  • Accuracy Fallacy : Accurate model does not mean correct model
  • How to create interpretable glassbox models using Explainable Boosting Machine ?
  • How Explainable Boosting Machine models work?
  • How to use interpret-ml library to obtain globally and locally important features?
  • Case Study on probing, de-bugging, comapring two different models using interpret-ml
  • Using Microsoft's 'Design Probe Thinking'