Applying our learning
This chapter’s Applying our learning section focuses on getting your Databricks workspace set up and ready for each project we’ll be working through. We’ll also go over getting set up in Kaggle so that you can download the datasets we will use throughout the rest of this book. Let’s get started!
Technical requirements
Before we begin setting up a workspace, please review the technical requirements needed to complete the hands-on work in this chapter:
- We utilize a Python package,
opendatasets, to download the data we need from the Kaggle API easily. - We use the Databricks Labs Python library,
dbldatagen, to generate synthetic data. - To use the Kaggle API, you must download your credential file,
kaggle.json. - A GitHub account is beneficial for connecting Databricks and the code repository for the book (https://github.com/PacktPublishing/Databricks-ML-In-Action). In addition to a GitHub account, it is ideal to fork...
