In this chapter, we looked at the capabilities of the MLlib package of PySpark. Even though the package is currently in a maintenance mode and is not actively being worked on, it is still good to know how to use it. Also, for now it is the only package available to train models while streaming data. We used MLlib to clean up, transform, and get familiar with the dataset of infant deaths. Using that knowledge we then successfully built two models that aimed at predicting the chance of infant survival given the information about its mother, father, and place of birth.
In the next chapter, we will revisit the same problem, but using the newer package that is currently the Spark recommended package for machine learning.