{"product_id":"dive-into-deep-learning-paperback-softback-9781009389433","title":"Dive into Deep Learning (Paperback \/ softback) 9781009389433","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eDive into Deep Learning\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eAn approachable text combining the depth and quality of a textbook with the interactive multi-framework code of a hands-on tutorial.\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eAston Zhang (Author), Zachary C. Lipton (Author), Mu Li (Author), Alexander J. Smola (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781009389433, Cambridge University Press\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePaperback \/ softback, published 7 December 2023\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e574 pages\u003cbr\u003e25.4 x 20.3 x 2.5 cm, 1.38 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e'Dive into Deep Learning strikes an excellent balance between hands-on learning and in-depth explanation. I've used it in my deep learning course and recommend it to anyone who wants to develop a thorough and practical understanding of deep learning.' Colin Raffel, Assistant Professor, University of North Carolina, Chapel Hill\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eDeep learning has revolutionized pattern recognition, introducing tools that power a wide range of technologies in such diverse fields as computer vision, natural language processing, and automatic speech recognition. Applying deep learning requires you to simultaneously understand how to cast a problem, the basic mathematics of modeling, the algorithms for fitting your models to data, and the engineering techniques to implement it all. This book is a comprehensive resource that makes deep learning approachable, while still providing sufficient technical depth to enable engineers, scientists, and students to use deep learning in their own work. No previous background in machine learning or deep learning is required—every concept is explained from scratch and the appendix provides a refresher on the mathematics needed. Runnable code is featured throughout, allowing you to develop your own intuition by putting key ideas into practice.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eInstallation\u003cbr\u003e Notation\u003cbr\u003e 1. Introduction\u003cbr\u003e 2. Preliminaries\u003cbr\u003e 3. Linear neural networks for regression\u003cbr\u003e 4. Linear neural networks for classification\u003cbr\u003e 5. Multilayer perceptrons\u003cbr\u003e 6. Builders guide\u003cbr\u003e 7. Convolutional neural networks\u003cbr\u003e 8. Modern convolutional neural networks\u003cbr\u003e 9. Recurrent neural networks\u003cbr\u003e 10. Modern recurrent neural networks\u003cbr\u003e 11. Attention mechanisms and transformers\u003cbr\u003e Appendix. Tools for deep learning\u003cbr\u003e Bibliography\u003cbr\u003e Index.\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Pattern recognition [\u003ca title=\"See our other books on Pattern recognition\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Pattern%20recognition%20%5BUYQP%5D%22\"\u003eUYQP\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Cambridge University Press","offers":[{"title":"Brand New","offer_id":52165307334936,"sku":"9781009389433","price":25.35,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781009389433i.jpg?v=1781098168","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/dive-into-deep-learning-paperback-softback-9781009389433","provider":"Freshly Printed Books","version":"1.0","type":"link"}