Master the art of bringing deep learning models from research to reality with "Deep Learning Patterns and Practices" by Andrew Ferlitsch. This comprehensive guide provides best practices, reproducible architectures, and essential design patterns to seamlessly integrate deep learning into your software projects. Discover: * The internal workings of modern convolutional neural networks (CNNs) * Procedural reuse design patterns for CNN architectures * Models optimized for mobile and IoT devices * Strategies for assembling large-scale model deployments * Techniques for optimizing hyperparameter tuning * Steps for migrating models to production environments Written by deep learning expert Andrew Ferlitsch, this book translates complex concepts into accessible diagrams and code samples, saving you valuable time and effort. Ideal for machine learning engineers familiar with Python and deep learning. Product Summary: Deep Learning Patterns and Practices, Paperback, 472 pages, English, ISBN 9781617298264, authored by Andrew Ferlitsch, published by Manning Publications.