Chapter 5: Parallel Training with TPOT and Dask
In this chapter, you'll dive into a bit of a more advanced topic; that is, automated machine learning. You'll learn how to handle machine learning tasks in a parallel manner by distributing the work on a Dask cluster. This chapter will be more theoretical than the previous two, but you will still learn many useful things.
We'll cover essential topics and ideas behind parallelism in Python, and you'll learn how to achieve parallelism in a couple of different ways. Then, we'll dive deep into the Dask library, explore its basic functionality, and see how you can tie it with TPOT.
This chapter will cover the following topics:
- Introduction to parallelism in Python
- Introduction to the Dask library
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