{"product_id":"deep-learning-design-patterns","title":"Deep Learning Design Patterns","description":"\u003cdiv class=\"product-section\" style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e  \u003cdiv class=\"description-body\" style=\"text-align: left;margin-bottom: 21.0px;\"\u003e   Deep learning has revealed ways to create algorithms for applications that we never dreamed were possible. For software developers, the challenge lies in taking cutting-edge technologies from R\u0026amp;D labs through to production.   \u003cspan\u003e \u003c\/span\u003e   \u003ci style=\"\"\u003eDeep Learning Design Patterns\u003c\/i\u003e   \u003cspan\u003e \u003c\/span\u003eis here to help. 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. Written by Google deep learning expert Andrew Ferlitsch, it''s filled with the latest deep learning insights and best practices from his work with Google Cloud AI. Each valuable technique is presented in a way that''s easy to understand and filled with accessible diagrams and code samples.  \u003c\/div\u003e \u003c\/div\u003e \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e  \u003ch2 style=\"color: inherit;text-transform: lowercase;line-height: 1.1;font-size: 27.0px;font-weight: 300;margin-top: 42.0px;margin-bottom: 10.5px;\"\u003eabout the technology\u003c\/h2\u003eYou don''t need to design your deep learning applications from scratch! By viewing cutting-edge deep learning models as design patterns, developers can speed up their creation of AI models and improve model understandability for both themselves and other users. \u003c\/div\u003e \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e  \u003ch2 style=\"color: inherit;text-transform: lowercase;line-height: 1.1;font-size: 27.0px;font-weight: 300;margin-top: 42.0px;margin-bottom: 10.5px;\"\u003eabout the book\u003c\/h2\u003e  \u003ci style=\"\"\u003eDeep Learning Design Patterns\u003c\/i\u003e  \u003cspan\u003e \u003c\/span\u003edistills models from the latest research papers into practical design patterns applicable to enterprise AI projects. Using diagrams, code samples, and easy-to-understand language, Google Cloud AI expert Andrew Ferlitsch shares insights from state-of-the-art neural networks. You''ll learn how to integrate design patterns into deep learning systems from some amazing examples, including a real-estate program that can evaluate house prices just from uploaded photos and a speaking AI capable of delivering live sports broadcasting. Building on your existing deep learning knowledge, you''ll quickly learn to incorporate the very latest models and techniques into your apps as idiomatic, composable, and reusable design patterns. \u003c\/div\u003e \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e    \u003c\/div\u003e \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e  \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e   \u003ch2 style=\"color: inherit;text-transform: lowercase;line-height: 1.1;font-size: 27.0px;font-weight: 300;margin-top: 42.0px;margin-bottom: 10.5px;\"\u003ewhat''s inside\u003c\/h2\u003e   \u003cul style=\"margin-top: 0.0px;margin-bottom: 10.5px;\"\u003e    \u003cli style=\"\"\u003eInternal functioning of modern convolutional neural networks\u003c\/li\u003e    \u003cli style=\"\"\u003eProcedural reuse design pattern for CNN architectures\u003c\/li\u003e    \u003cli style=\"\"\u003eModels for mobile and IoT devices\u003c\/li\u003e    \u003cli style=\"\"\u003eComposable design pattern for automatic learning methods\u003c\/li\u003e    \u003cli style=\"\"\u003eAssembling large-scale model deployments\u003c\/li\u003e    \u003cli style=\"\"\u003eComplete code samples and example notebooks\u003c\/li\u003e    \u003cli style=\"\"\u003eAccompanying YouTube videos\u003c\/li\u003e   \u003c\/ul\u003e  \u003c\/div\u003e  \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e   \u003ch2 style=\"color: inherit;text-transform: lowercase;line-height: 1.1;font-size: 27.0px;font-weight: 300;margin-top: 42.0px;margin-bottom: 10.5px;\"\u003eabout the reader\u003c\/h2\u003eFor machine learning engineers familiar with Python and deep learning.  \u003c\/div\u003e  \u003cdiv style=\"color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacing: normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacing: 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);\"\u003e   \u003ch2 style=\"color: inherit;text-transform: lowercase;line-height: 1.1;font-size: 27.0px;font-weight: 300;margin-top: 42.0px;margin-bottom: 10.5px;\"\u003eabout the author\u003c\/h2\u003e   \u003ci style=\"\"\u003eAndrew Ferlitsch\u003c\/i\u003e   \u003cspan\u003e \u003c\/span\u003eis an expert on computer vision and deep learning at Google Cloud AI Developer Relations. He was formerly a principal research scientist for 20 years at Sharp Corporation of Japan, where he amassed 115 US patents and worked on emerging technologies in telepresence, augmented reality, digital signage, and autonomous vehicles. In his present role, he reaches out to developer communities, corporations and universities, teaching deep learning and evangelizing Google''s AI technologies.  \u003c\/div\u003e \u003c\/div\u003e","brand":"MediaPlace","offers":[{"title":"Default Title","offer_id":57314725233022,"sku":"NW9781617298264","price":53.95,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1379\/1261\/files\/9781617298264.jpg?v=1778714190","url":"https:\/\/mediaplace.com\/en-eu\/products\/deep-learning-design-patterns","provider":"MediaPlace","version":"1.0","type":"link"}