| 書目名稱 | Deep Learning | | 副標(biāo)題 | Foundations and Conc | | 編輯 | Christopher M. Bishop,Hugh Bishop | | 視頻video | http://file.papertrans.cn/265/264563/264563.mp4 | | 概述 | Foundational and conceptual approach emphasizes real-world practical value of techniques for a wide range of learners.Companion volume to the author‘s standard reference text Pattern Recognition and M | | 圖書封面 |  | | 描述 | .This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation for potential future specialization. The field of deep learning is undergoing rapid evolution, and therefore this book focusses on ideas that are likely to endure the test of time..The book is organized into numerous bite-sized chapters, each exploring a distinct topic, and the narrative follows a linear progression, with each chapter building upon content from its predecessors. This structure is well-suited to teaching a two-semester undergraduate or postgraduate machine learning course, while remaining equally relevant to those engaged in active research or in self-study..A full understanding of machine learning requires some mathematical background and so the book includes a self-contained introduction to probability theory. However, the focus of the book is on conveying a clear understanding of ideas, with emphasis on the real-world practical value | | 出版日期 | Textbook 2024 | | 關(guān)鍵詞 | machine learning; Deep learning; Neural networks; Decision theory; Directed graphical models; Convolution | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-45468-4 | | isbn_ebook | 978-3-031-45468-4 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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