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Hands-On Explainable AI (XAI) with Python

You're reading from Hands-On Explainable AI (XAI) with Python Interpret, visualize, explain, and integrate reliable AI for fair, secure, and trustworthy AI apps

Product type Paperback

Published in Jul 2020

Publisher Packt

ISBN-13 9781800208131

Length 454 pages

Edition 1st Edition

Languages

Python

Concepts

Artificial Intelligence

Author (1):

Denis Rothman

View More author details

Table of Contents (16) Chapters

Preface

1. Explaining Artificial Intelligence with Python

2. White Box XAI for AI Bias and Ethics FREE CHAPTER

3. Explaining Machine Learning with Facets

4. Microsoft Azure Machine Learning Model Interpretability with SHAP

5. Building an Explainable AI Solution from Scratch

6. AI Fairness with Google's What-If Tool (WIT)

7. A Python Client for Explainable AI Chatbots

8. Local Interpretable Model-Agnostic Explanations (LIME)

9. The Counterfactual Explanations Method

10. Contrastive XAI

11. Anchors XAI

12. Cognitive XAI

13. Answers to the Questions

14. Other Books You May Enjoy

15. Index

Further reading

For more on the CEM:

Explanations Based on the Missing: Toward Contrastive Explanations with Pertinent Negatives, by Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Paishun Ting, Karthikeyan Shanmugam, and Payel Das: https://arxiv.org/abs/1802.07623
The AI Explainability 360 toolkit contains the definitive implementation of the contrastive explanations method, and can be found at http://aix360.mybluemix.net/

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Authors (1)

Denis Rothman

Denis Rothman

Expert in AI Transformers including ChatGPT/GPT-4, Bestselling Author

See other products by Denis Rothman

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