Software Engineer's Guide to Deep Learning System Design (MEAP V08)

Design systems optimized for deep learning models. Written for software engineers, this book teaches you how to implement a maintainable platform for developing deep learning models.

In Software Engineer's Guide to Deep Learning System Design you will learn how to

Transfer your software development skills to deep learning systems
Recognize and solve common engineering challenges for deep learning systems
Understand the deep learning development cycle
Automate training for models in TensorFlow and PyTorch
Optimize dataset management, training, model serving and hyperparameter tuning
Pick the right open-source project for your platform
Software Engineer's Guide to Deep Learning System Design is a practical guide for software engineers and data scientists who are designing and building platforms for deep learning. It’s full of hands-on examples that will help you transfer your software development skills to implementing deep learning platforms. You’ll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting—and lucrative—career as a deep learning engineer.

about the technology
Behind every deep learning researcher is a team of engineers bringing their models to production. To build these systems, you need to understand how a deep learning system’s platform differs from other distributed systems. By mastering the core ideas in this book, you’ll be able to support deep learning systems in a way that’s fast, repeatable, and reliable.

about the book
Software Engineer's Guide to Deep Learning System Design teaches you to design and implement an automated platform to support creating, training, and maintaining deep learning models. In it, you’ll learn just enough about deep learning to understand the needs of the data scientists who will be using your system. You’ll learn to gather requirements, translate them into system component design choices, and integrate those components into a cohesive whole. A complete example system and insightful exercises help you build an intuitive understanding of DL system design.