| 书目名称 | Deep Learning: Fundamentals, Theory and Applications | | 编辑 | Kaizhu Huang,Amir Hussain,Rui Zhang | | 视频video | | | 概述 | Provides thorough background of deep learning.Introduces widely-used learning architectures and algorithms.Includes new theory and applications of deep learning | | 丛书名称 | Cognitive Computation Trends | | 图书封面 |  | | 描述 | .The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. .Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field.. .This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in stud | | 出版日期 | Book 2019 | | 关键词 | Neural networks; Deep representation; Learning; Optimization; Artificial intelligence; Cognitively-inspir | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-06073-2 | | isbn_ebook | 978-3-030-06073-2Series ISSN 2524-5341 Series E-ISSN 2524-535X | | issn_series | 2524-5341 | | copyright | Springer Nature Switzerland AG 2019 |
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发表于 2025-3-21 19:40:15
