| 书目名称 | Deep Learning for NLP and Speech Recognition | | 编辑 | Uday Kamath,John Liu,James Whitaker | | 视频video | | | 概述 | A comprehensive resource that builds up from elementary deep learning, text, and speech principles to advanced state-of-the-art neural architectures.A ready reference for deep learning techniques appl | | 图书封面 |  | | 描述 | This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. .Deep Learning for NLP and Speech Recognition. explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. .Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. .The book is organized into three parts, aligning to different groups of readers and their | | 出版日期 | Textbook 2019 | | 关键词 | Deep Learning Architecture; Document Classification; Machine Translation; Language Modeling; Speech Reco | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-14596-5 | | isbn_softcover | 978-3-030-14598-9 | | isbn_ebook | 978-3-030-14596-5 | | copyright | Springer Nature Switzerland AG 2019 |
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发表于 2025-3-21 18:46:21
