Name: Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python
Price: 34.21 EUR
Availability: InStock
Author: Mishra, Pradeepta
ISBN: 9781484290286

portada Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python

Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python

Type

Physical Book

Author

Pradeepta Mishra

Publisher

Apress

Language

English

Pages

254

Format

Paperback

Dimensions

23.4 x 15.6 x 1.5 cm

Weight

0.39 kg.

ISBN13

9781484290286

Synopsis "Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python"

Understand how to use Explainable AI (XAI) libraries and build trust in AI and machine learning models. This book utilizes a problem-solution approach to explaining machine learning models and their algorithms. The book starts with model interpretation for supervised learning linear models, which includes feature importance, partial dependency analysis, and influential data point analysis for both classification and regression models. Next, it explains supervised learning using non-linear models and state-of-the-art frameworks such as SHAP values/scores and LIME for local interpretation. Explainability for time series models is covered using LIME and SHAP, as are natural language processing-related tasks such as text classification, and sentiment analysis with ELI5, and ALIBI. The book concludes with complex model classification and regression-like neural networks and deep learning models using the CAPTUM framework that shows feature attribution, neuron attribution, and activation attribution. After reading this book, you will understand AI and machine learning models and be able to put that knowledge into practice to bring more accuracy and transparency to your analyses. What You Will LearnCreate code snippets and explain machine learning models using PythonLeverage deep learning models using the latest code with agile implementationsBuild, train, and explain neural network models designed to scaleUnderstand the different variants of neural network models Who This Book Is ForAI engineers, data scientists, and software developers interested in XAI

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Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python - Mishra, Pradeepta

Synopsis "Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python"

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