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Deep Learning Design Patterns

Deep Learning Design Patterns distills models from the latest research papers into practical design patterns applicable to enterprise AI projects. You'll learn how to integrate design patterns into deep learning systems from some amazing examples, using diagrams, code samples, and easy-to-understand language.

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&D labs through to production. Deep Learning Design Patterns, is 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.

Deep Learning Design Patterns distills models from the latest research papers into practical design patterns applicable to enterprise AI projects. You'll learn how to integrate design patterns into deep learning systems from some amazing examples, using diagrams, code samples, and easy-to-understand language. 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.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

 

Andrew Ferlitsch is 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.