Explainable-AI

Explainable AI
Preface
How to use this book?
Contents
What is Explainable AI?
Why do we need Explainablity?
Explainable systems and Black box systems
Types of Explainability Techniques
Explainable Models
- Linear Regression
  Assumptions
  Model
  Statistical Interpretation
- Decision Trees
  How Do They Work?
  Creating the model
  Interpretation
Explainability Techniques for Classical ML
Datasets
Implementation of these techniques on different models
Future scope
Contributors
Citing this Book

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Restructuring of the book is in progress, updates will follow in the last week of December

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