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Deep Learning Patterns and Practices

Andrew Ferlitsch
  • MEAP began July 2020
  • Publication in September 2021 (estimated)
  • ISBN 9781617298264
  • 400 pages (estimated)
  • printed in black & white
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A definitive guide to best practices in developing deep learning applications.

Dr. Brian R. Gaines
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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 Patterns and Practices 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. 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.

about the technology

You 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.

about the book

Deep Learning Patterns and Practices distills 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. 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.

what's inside

  • Internal functioning of modern convolutional neural networks
  • Procedural reuse design pattern for CNN architectures
  • Models for mobile and IoT devices
  • Assembling large-scale model deployments
  • Complete code samples and example notebooks
  • Accompanying YouTube videos

about the reader

For machine learning engineers familiar with Python and deep learning.

about the author

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.

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Probably one of the best written books about the topic. This could become what the Gang of Four Design Patterns book is for developers.

Ariel Gamino

A must read book for all deep learning practitioners and beginners who want to step into the world of AI!

Udendran Mudaliyar

The author uses a brilliant and unique approach to teaching and helping the audience understanding the material, putting real deep learning models in terms of design patterns.

Christopher Marshall

Andrew is a first-class expert in this field. His style and way of explaining complex ideas are brilliant.

Ninoslav Cerkez

A great resource for thinking about how to approach developing deep learning models in a very plug-n-play extendable way.

Nick Vazquez

Awesome book. Covers the entire spectrum of deep learning in detail.

Romit Singhai

The author clearly possesses a mastery of the state of AI. The book took my knowledge to the next level by demonstrating principles and explanations as to why models are composed the way they are.

Curtis Bates