EBOOK

Deep Learning Patterns and Practices

Andrew Ferlitsch
(0)
Pages
472
Year
2021
Language
English

About

Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production.

In Deep Learning Patterns and Practices you will learn:

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

Optimizing hyperparameter tuning

Migrating a model to a production environment

The big challenge of deep learning lies in taking cutting-edge technologies from R&D labs through to production. Deep Learning Patterns and Practices 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.

Deep Learning Patterns and Practices 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.

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