{"product_id":"9781617298264","title":"Deep Learning Patterns and Practices","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=\"\"\u003eFerlitsch, Andrew\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\u003e10\/5\/2021\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\u003eDiscover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eIn \u003ci\u003eDeep Learning Patterns and Practices\u003c\/i\u003e you will learn:\u003cbr\u003e\u003cbr\u003eInternal functioning of modern convolutional neural networks\u003cbr\u003eProcedural reuse design pattern for CNN architectures\u003cbr\u003eModels for mobile and IoT devices\u003cbr\u003eAssembling large-scale model deployments\u003cbr\u003eOptimizing hyperparameter tuning\u003cbr\u003eMigrating a model to a production environment\u003cbr\u003e\u003cbr\u003eThe big challenge of deep learning lies in taking cutting-edge technologies from R\u0026amp;D labs through to production. \u003ci\u003eDeep Learning Patterns and Practices\u003c\/i\u003e is here to help. This unique guide lays out the latest deep learning insights from author Andrew Ferlitsch’s work with Google Cloud AI. In it, you'll find deep learning models presented in a unique new way: as extendable design patterns you can easily plug-and-play into your software projects. Each valuable technique is presented in a way that's easy to understand and filled with accessible diagrams and code samples.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the technology\u003c\/b\u003e\u003cbr\u003eDiscover best practices, design patterns, and reproducible architectures that will guide your deep learning projects from the lab into production. This awesome book collects and illuminates the most relevant insights from a decade of real world deep learning experience. You’ll build your skills and confidence with each interesting example.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the book\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eDeep Learning Patterns and Practices\u003c\/i\u003e is a deep dive into building successful deep learning applications. You’ll save hours of trial-and-error by applying proven patterns and practices to your own projects. Tested code samples, real-world examples, and a brilliant narrative style make even complex concepts simple and engaging. Along the way, you’ll get tips for deploying, testing, and maintaining your projects.\u003cbr\u003e\u003cbr\u003eWhat's inside\u003cbr\u003e\u003cbr\u003eModern convolutional neural networks\u003cbr\u003eDesign pattern for CNN architectures\u003cbr\u003eModels for mobile and IoT devices\u003cbr\u003eLarge-scale model deployments\u003cbr\u003eExamples for computer vision\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the reader\u003c\/b\u003e\u003cbr\u003eFor machine learning engineers familiar with Python and deep learning.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eAndrew Ferlitsch\u003c\/b\u003e is an expert on computer vision, deep learning, and operationalizing ML in production at Google Cloud AI Developer Relations.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003ePART 1 DEEP LEARNING FUNDAMENTALS\u003cbr\u003e1 Designing modern machine learning\u003cbr\u003e2 Deep neural networks\u003cbr\u003e3 Convolutional and residual neural networks\u003cbr\u003e4 Training fundamentals\u003cbr\u003ePART 2 BASIC DESIGN PATTERN\u003cbr\u003e5 Procedural design pattern\u003cbr\u003e6 Wide convolutional neural networks\u003cbr\u003e7 Alternative connectivity patterns\u003cbr\u003e8 Mobile convolutional neural networks\u003cbr\u003e9 Autoencoders\u003cbr\u003ePART 3 WORKING WITH PIPELINES\u003cbr\u003e10 Hyperparameter tuning\u003cbr\u003e11 Transfer learning\u003cbr\u003e12 Data distributions\u003cbr\u003e13 Data pipeline\u003cbr\u003e14 Training and deployment pipeline","brand":"Manning","offers":[{"title":"Default Title","offer_id":48176692789503,"sku":"9781617298264","price":59.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0452\/0886\/2873\/files\/Jacket_a5a65f17-e5a4-4cc9-91c6-7d92a3cb7724.jpg?v=1771351514","url":"https:\/\/massivebookshop.com\/de\/products\/9781617298264","provider":"MASSIVE BOOKSHOP","version":"1.0","type":"link"}