To be practically usable, a deep learning model must be built into a software platform. As a software engineer, you need a deep understanding of deep learning to create such a system. This book gives you that depth. Designing Deep Learning Systems: A guide for software engineers teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer's perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you'll need to build your own maintainable, efficient, and scalable deep learning platforms. What's Inside The deep learning development cycle, Automate training in TensorFlow and PyTorch, Dataset management, model serving, and hyperparameter tuning, A hands-on deep learning lab For software developers and engineering-minded data scientists. Examples in Java and Python.