{"product_id":"deep-learning-for-nlp-and-uday-kamath-9783030145989","title":"Deep Learning for Nlp and Speech Recognition","description":"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. \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. \u003cbr\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. \u003cbr\u003eThe book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: \u003cbr\u003e \u003cp\u003e \u003cb\u003eMachine Learning, NLP, and Speech Introduction\u003c\/b\u003e\u003c\/p\u003e \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 \u003cp\u003e \u003cb\u003eDeep Learning Basics\u003c\/b\u003e\u003c\/p\u003e \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 \u003cp\u003e \u003cb\u003eAdvanced Deep Learning Techniques for Text and Speech\u003c\/b\u003e\u003c\/p\u003e The third part has \u003cb\u003efive chapters\u003c\/b\u003e that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Uday Kamath, John Liu, James Whitaker\u003cbr\u003e\u003cb\u003eISBN-10:\u003c\/b\u003e 3030145980\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9783030145989\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Springer\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 08\/14\/2020\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 621\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 2.45lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 10.00h x 7.00w x 1.31d","brand":"Uday Kamath","offers":[{"title":"Paperback","offer_id":43993405063423,"sku":"9783030145989","price":89.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_081110bf-0fa1-4bd8-a9b3-0dd991877a5d.jpg?v=1683324166","url":"https:\/\/www.whiterainbookhouse.com\/products\/deep-learning-for-nlp-and-uday-kamath-9783030145989","provider":"WR Book House","version":"1.0","type":"link"}