{"product_id":"9781617298639","title":"Inside Deep Learning: Math, Algorithms, Models","description":"\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eAuthor\/Contributor(s):\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003eRaff, Edward\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003ePublisher:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eManning\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eDate:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e5\/31\/2022\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eBinding:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003ePaperback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003eNEW\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\u003cb\u003eJourney through the theory and practice of modern deep learning, and apply innovative techniques to solve everyday data problems.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eIn \u003ci\u003eInside Deep Learning\u003c\/i\u003e, you will learn how to:\u003cbr\u003e\u003cbr\u003eImplement deep learning with PyTorch\u003cbr\u003eSelect the right deep learning components\u003cbr\u003eTrain and evaluate a deep learning model\u003cbr\u003eFine tune deep learning models to maximize performance\u003cbr\u003eUnderstand deep learning terminology\u003cbr\u003eAdapt existing PyTorch code to solve new problems\u003cbr\u003e\u003cbr\u003e\u003ci\u003eInside Deep Learning\u003c\/i\u003e is an accessible guide to implementing deep learning with the PyTorch framework. It demystifies complex deep learning concepts and teaches you to understand the vocabulary of deep learning so you can keep pace in a rapidly evolving field. No detail is skipped—you’ll dive into math, theory, and practical applications. Everything is clearly explained in plain English.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the technology\u003c\/b\u003e\u003cbr\u003eDeep learning doesn’t have to be a black box! Knowing how your models and algorithms actually work gives you greater control over your results. And you don’t have to be a mathematics expert or a senior data scientist to grasp what’s going on inside a deep learning system. This book gives you the practical insight you need to understand and explain your work with confidence.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the book\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eInside Deep Learning\u003c\/i\u003e illuminates the inner workings of deep learning algorithms in a way that even machine learning novices can understand. You’ll explore deep learning concepts and tools through plain language explanations, annotated code, and dozens of instantly useful PyTorch examples. Each type of neural network is clearly presented without complex math, and every solution in this book can run using readily available GPU hardware!\u003cbr\u003e\u003cbr\u003eWhat's inside\u003cbr\u003e\u003cbr\u003eSelect the right deep learning components\u003cbr\u003eTrain and evaluate a deep learning model\u003cbr\u003eFine tune deep learning models to maximize performance\u003cbr\u003eUnderstand deep learning terminology\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the reader\u003c\/b\u003e\u003cbr\u003eFor Python programmers with basic machine learning skills.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eEdward Raff\u003c\/b\u003e is a Chief Scientist at Booz Allen Hamilton, and the author of the JSAT machine learning library.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePART 1 FOUNDATIONAL METHODS\u003cbr\u003e1 The mechanics of learning\u003cbr\u003e2 Fully connected networks\u003cbr\u003e3 Convolutional neural networks\u003cbr\u003e4 Recurrent neural networks\u003cbr\u003e5 Modern training techniques\u003cbr\u003e6 Common design building blocks\u003cbr\u003ePART 2 BUILDING ADVANCED NETWORKS\u003cbr\u003e7 Autoencoding and self-supervision\u003cbr\u003e8 Object detection\u003cbr\u003e9 Generative adversarial networks\u003cbr\u003e10 Attention mechanisms\u003cbr\u003e11 Sequence-to-sequence\u003cbr\u003e12 Network design alternatives to RNNs\u003cbr\u003e13 Transfer learning\u003cbr\u003e14 Advanced building blocks","brand":"Manning","offers":[{"title":"Default Title","offer_id":42973611163903,"sku":"9781617298639","price":59.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0452\/0886\/2873\/files\/Jacket_1b6a0455-2386-4fef-8491-5360cc74e936.jpg?v=1771351351","url":"https:\/\/massivebookshop.com\/products\/9781617298639","provider":"MASSIVE BOOKSHOP","version":"1.0","type":"link"}