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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Explainable AI with Python
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Explainable AI with Python
Antonio Di Cecco (Taschenbuch, Englisch)
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Beschreibung
This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linear and logistic regression, deep learning neural networks, natural language processing and image recognition, among the others.
Progress in Machine Learning is… increasing the use of artificial agents to perform critical tasks previously handled by humans (healthcare, legal and finance, among others). While the principles that guide the design of these agents are understood, most of the current deep-learning models are "opaque" to human understanding. Explainable AI with Python fills the current gap in literature on this emerging topic by taking both a theoretical and a practical perspective, making the reader quickly capable of working with tools and code for Explainable AI.
Beginning with examples of what Explainable AI (XAI) is and why it is needed in the field, the book details different approaches to XAI depending on specific context and need. Hands-on work on interpretable models with specific examples leveraging Python are then presented, showing how intrinsic interpretable models can be interpreted and how to produce “human understandable” explanations. Model-agnostic methods for XAI are shown to produce explanations without relying on ML models internals that are “opaque.” Using examples from Computer Vision, the authors then look at explainable models for Deep Learning and prospective methods for the future. Taking a practical perspective, the authors demonstrate how to effectively use ML and XAI in science. The final chapter explains Adversarial Machine Learning and how to do XAI with adversarial examples. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
01.01.2021
Sprache
Englisch
EAN
9783030686390
Herausgeber
Springer International Publishing
Sonderedition
Nein
Autor
Antonio Di Cecco
Seitenanzahl
202
Auflage
1st edition 2021
Einbandart
Taschenbuch
Schlagwörter
XAI, Artificial Intelligence, Machine Learning, intrinsic interpretable models, Shapley Values, Deep Taylor Decomposition
Thema-Inhalt
UYQ - Künstliche Intelligenz
UYQM - Maschinelles Lernen
UMX - Programmier- und Skriptsprachen, allgemein
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer Nature Customer Service Center GmbH, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com
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