| 書(shū)目名稱 | Computational Methods for Deep Learning | | 副標(biāo)題 | Theoretic, Practice | | 編輯 | Wei Qi Yan | | 視頻video | http://file.papertrans.cn/233/232712/232712.mp4 | | 概述 | Introduce deep learning from mathematical viewpoint.Review mathematical methods in Bachelor and Master’s degree level.Detail mathematical approaches to resolve deep learning problems.Provide methodolo | | 叢書(shū)名稱 | Texts in Computer Science | | 圖書(shū)封面 |  | | 描述 | .Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations..Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms..As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learni | | 出版日期 | Textbook 20211st edition | | 關(guān)鍵詞 | Deep Learning; Machine Learning; Pattern Analysis; Manifold Learning; Machine Vision; Reinforcement Learn | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-61081-4 | | isbn_softcover | 978-3-030-61083-8 | | isbn_ebook | 978-3-030-61081-4Series ISSN 1868-0941 Series E-ISSN 1868-095X | | issn_series | 1868-0941 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
The information of publication is updating
|
|
|Archiver|手機(jī)版|小黑屋|
派博傳思國(guó)際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-10-8 21:46
發(fā)表于 2025-3-21 17:18:07
