In this chapter, we will use concepts and apply tools related to common topics in data science and optimization tasks. We will assume that you already have a good understanding of concepts such as neural networks and hyperparameter tuning, and also general knowledge of machine learning frameworks such as TensorFlow, PyTorch, or Keras.
In this chapter, we will discuss various techniques in order to distribute and optimize the training of deep learning models using Azure Databricks, so if you are not familiar with these terms, it would be advisable for you to review the TensorFlow documentation on how neural networks are designed and trained.
In order to work on the examples given in this chapter, you will need to have the following:
- An Azure Databricks subscription.
- An Azure Databricks notebook attached to a running cluster with Databricks Runtime ML version 7.0 or higher.