Section 4: PyTorch in Production Systems

In this section, we will explore how to use PyTorch as a powerful tool for running light to extremely heavy deep learning applications. We'll then explore the journey of building a model and putting it into a live production system while grasping some optimization tricks along the way. We'll also dig deeper into the topics of neural architecture search, as well as explainability in AI. The final chapter of this book covers the various additional tools that can be used to accelerate model prototyping and productionizing in PyTorch.

Upon completing this section, you will have an understanding of using PyTorch in production systems at industrial scale. You will be further equipped with the latest PyTorch tools such as Captum and fast.ai and skills such as distributed training and AutoML that are crucial for building advanced deep learning systems.

This section comprises the following chapters:

• Chapter 10, Operationalizing PyTorch Models into Production
• Chapter 11, Distributed Training
• Chapter 12, PyTorch and AutoML
• Chapter 13, PyTorch and Explainable AI
• Chapter 14, Rapid Prototyping with PyTorch