We’ve covered a lot of the basics in the book so far. But there are a lot of things we haven’t touched upon or dove into enough. In this chapter, we’ll look at a few things that are worth looking at so you know what’s available.
To start with, we’ll look at machine learning. It’s the topic de jour, and you might imagine that Apache Spark is very well suited for it. We’ll take a quick look at MLlib, a library that is especially well suited for running these types of load on Databricks.
Next, we’ll look at a Databricks-backed feature called MLflow. It’s a functionality that ...
