Description: Practical Explainable AI Using Python : Artificial Intelligence Model Explanations Using Python-Based Libraries, Extensions, and Frameworks, Paperback by Mishra, Pradeepta, ISBN 1484271572, ISBN-13 9781484271575, Like New Used, Free shipping in the US Learn the ins and outs of decisions, biases, and reliability of AI algorithms and how to make sense of these predictions. This book explores the so-called black-box models to boost the adaptability, interpretability, and explainability of the decisions made by AI algorithms using frameworks such as Python XAI libraries, TensorFlow , Keras, and custom frameworks using Python wrappers.
- Review the different ways of making an AI model interpretable and explainable
- Examine the biasness and good ethical practices of AI models
- Quantify, visualize, and estimate reliability of AI models
- Design frameworks to unbox the black-box models
- Assess the fairness of AI models
- Understand the building blocks of trust in AI models
- Increase the level of AI adoption
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Book Title: Practical Explainable AI Using Python : Artificial Intelligence M
Number of Pages: Xviii, 344 Pages
Publication Name: Practical Explainable AI Using Python : Artificial Intelligence Model Explanations Using Python-Based Libraries, Extensions, and Frameworks
Language: English
Publisher: Apress L. P.
Subject: Intelligence (Ai) & Semantics, Programming Languages / Python
Publication Year: 2021
Type: Textbook
Item Weight: 24.4 Oz
Item Length: 10 in
Author: Pradeepta Mishra
Subject Area: Computers
Item Width: 7 in
Format: Trade Paperback