Distributed Data Systems with Azure Databricks

Chapter 9: Databricks Runtime for Deep Learning

This chapter will take a deep dive into the development of classic deep learning algorithms to train and deploy models based on unstructured data, exploring libraries and algorithms as well. The examples will be focused on the particularities and advantages of using Databricks for DL, creating DL models. In this chapter, we will learn about how we can efficiently train deep learning models in Azure Databricks and implementations of the different libraries that we have available to use.

The following topics will be introduced in this chapter:

• Loading data for deep learning
• Managing data using TFRecords
• Automating scheme inference
• Using Petastorm for distributed learning
• Reading a dataset
• Data ...