{"product_id":"9783030145989","title":"Deep Learning for NLP and Speech Recognition","description":"\u003ch1\u003eDeep Learning for NLP and Speech Recognition\u003c\/h1\u003e \u003ch2\u003eKamath, Uday; Liu, John; Whitaker, James\u003c\/h2\u003e \u003cp\u003eThis 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. \u003ci\u003eDeep Learning for NLP and Speech Recognition\u003c\/i\u003e 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.  \u003c\/p\u003e\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\u003cdiv\u003eMany 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. \u003c\/div\u003e\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e\u003cdiv\u003eThe book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are:\u003cbr\u003e\n\u003c\/div\u003e \u003cp\u003e      \u003cb\u003eMachine Learning, NLP, and Speech Introduction\u003c\/b\u003e\u003c\/p\u003e\n\n\u003cp\u003eThe first part has \u003cb\u003ethree chapters \u003c\/b\u003ethat introduce readers to the fields of  NLP, speech recognition,  deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries.\u003c\/p\u003e\n\n\u003cp\u003e      \u003cb\u003eDeep Learning Basics\u003c\/b\u003e\u003c\/p\u003e\n\n\u003cp\u003eThe \u003cb\u003efive chapters\u003c\/b\u003e in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. \u003c\/p\u003e\n\n\u003cp\u003e      \u003cb\u003eAdvanced Deep Learning Techniques for Text and Speech\u003c\/b\u003e\u003c\/p\u003e\n\n\u003cdiv\u003e\t\tThe third part has \u003cb\u003efive chapters\u003c\/b\u003e that discuss the latest and cutting-edge research in \t\tthe areas of deep learning that intersect with NLP and speech. Topics including \t\tattention mechanisms, memory augmented networks, transfer learning, multi-task \t\tlearning, domain adaptation, reinforcement learning, and end-to-end deep learning for \t\tspeech recognition are covered using case studies. \u003c\/div\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2020-08-14\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003eISBN-13: 9783030145989\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-030-14596-5\u003c\/p\u003e \u003cp\u003eDimensions: 254cm x178cm\u003c\/p\u003e \u003cp\u003ePages: 621\u003c\/p\u003e ","brand":"Springer International Publishing","offers":[{"title":"Default Title","offer_id":45169195417740,"sku":"9783030145989","price":0.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783030145989.jpg?v=1776036007","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9783030145989","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}