书目名称 | Explainable AI: Foundations, Methodologies and Applications | 编辑 | Mayuri Mehta,Vasile Palade ,Indranath Chatterjee | 视频video | | 概述 | Written for beginners and advanced machine learning users, including engineers and researchers on AI and applications.Covers concepts such as black box models, transparency, interpretable machine lear | 丛书名称 | Intelligent Systems Reference Library | 图书封面 |  | 描述 | .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.. | 出版日期 | Book 2023 | 关键词 | Intelligent Systems; Artificial Intelligence; Explainable AI; Neural Networks; Deep Learning; Applied Mac | 版次 | 1 | doi | https://doi.org/10.1007/978-3-031-12807-3 | isbn_softcover | 978-3-031-12809-7 | isbn_ebook | 978-3-031-12807-3Series ISSN 1868-4394 Series E-ISSN 1868-4408 | issn_series | 1868-4394 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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