{"product_id":"deep-learning-for-natural-language-processing-9781617295447","title":"Deep Learning for Natural Language Processing","description":"\u003cdiv class=\"book-description\"\u003e\n\u003cp\u003e\u003cstrong\u003eDeep Learning for Natural Language Processing\u003c\/strong\u003e by Raaijmakers, Stephan. paperback edition. ISBN: 9781617295447.\u003c\/p\u003e\n\u003cp\u003eExplore the most challenging issues of natural language processing, and learn how to solve them with cutting-edge deep learning!\n\nInside Deep Learning for Natural Language Processing you’ll find a wealth of NLP insights, including:\n\nAn overview of NLP and deep learning\nOne-hot text representations\nWord embeddings\nModels for textual similarity\nSequential NLP\nSemantic role labeling\nDeep memory-based NLP\nLinguistic structure\nHyperparameters for deep NLP\n\nDeep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve \"human\" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms.\n\nPurchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.\n\nAbout the technology\nDeep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses.\n\nAbout the book\nDeep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You’ll learn to use state-of the-art tools and techniques including BERT and XLNET, multitask learning, and deep memory-based NLP. Fascinating examples give you hands-on experience with a variety of real world NLP applications. Plus, the detailed code discussions show you exactly how to adapt each example to your own uses!\n\nWhats inside\n\nImprove question answering with sequential NLP\nBoost performance with linguistic multitask learning\nAccurately interpret linguistic structure\nMaster multiple word embedding techniques\n\nAbout the reader\nFor readers with intermediate Python skills and a general knowledge of NLP. No experience with deep learning is required.\n\nAbout the author\nStephan Raaijmakers is professor of Communicative AI at Leiden University and a senior scientist at The Netherlands Organization for Applied Scientific Research (TNO).\n\nTable of Contents\nPART 1 INTRODUCTION\n1 Deep learning for NLP\n2 Deep learning and language: The basics\n3 Text embeddings\nPART 2 DEEP NLP\n4 Textual similarity\n5 Sequential NLP\n6 Episodic memory for NLP\nPART 3 ADVANCED TOPICS\n7 Attention\n8 Multitask learning\n9 Transformers\n10 Applications of Transformers: Hands-on with BERT\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Manning","offers":[{"title":"Default Title","offer_id":44954427424821,"sku":"ByrdShop_1617295442","price":34.46,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0627\/8139\/0901\/files\/9781617295447_0c64865b-cf53-4363-b78d-826aa799d49b.jpg?v=1778736799","url":"https:\/\/atxbooks.com\/products\/deep-learning-for-natural-language-processing-9781617295447","provider":"ATX Books","version":"1.0","type":"link"}