Explainable AI: Foundations, Methodologies and Applications
Language: English
Published by Springer International Publishing, 2023
Series: Book 188 of 188 - Intelligent Systems Reference Library
- Softcover
- New
Condition: New
£ 119.18
Quantity: Over 20 available
Add to basketItem description from seller
Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Written for beginners and advanced machine learning users, including engineers and researchers on AI and applicationsCovers concepts such as black box models, transparency, interpretable machine learning and explanationsPresents evaluation .
Seller Inventory # 1128556062
- Title
- Explainable AI: Foundations, Methodologies and Applications
- Publisher
- Springer International Publishing
- Publication year
- 2023
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 3031128095
- ISBN 13
- 9783031128097
- Series
- Book 188 of 188: Intelligent Systems Reference Library
This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.
The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.
The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.
"About the title" may belong to another edition of this title.
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