Book Image

Machine Learning Automation with TPOT

By : Dario Radečić
Book Image

Machine Learning Automation with TPOT

By: Dario Radečić

Overview of this book

The automation of machine learning tasks allows developers more time to focus on the usability and reactivity of the software powered by machine learning models. TPOT is a Python automated machine learning tool used for optimizing machine learning pipelines using genetic programming. Automating machine learning with TPOT enables individuals and companies to develop production-ready machine learning models cheaper and faster than with traditional methods. With this practical guide to AutoML, developers working with Python on machine learning tasks will be able to put their knowledge to work and become productive quickly. You'll adopt a hands-on approach to learning the implementation of AutoML and associated methodologies. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will show you how to build automated classification and regression models and compare their performance to custom-built models. As you advance, you'll also develop state-of-the-art models using only a couple of lines of code and see how those models outperform all of your previous models on the same datasets. By the end of this book, you'll have gained the confidence to implement AutoML techniques in your organization on a production level.
Table of Contents (14 chapters)
1
Section 1: Introducing Machine Learning and the Idea of Automation
3
Section 2: TPOT – Practical Classification and Regression
8
Section 3: Advanced Examples and Neural Networks in TPOT

Q&A

  1. Define the term "parallelism."
  2. Explain which types of tasks can and can't be parallelized.
  3. List and explain three options for implementing parallelism in your applications (all are listed in this chapter).
  4. What is Dask and what makes it superior to NumPy and pandas for larger datasets?
  5. Name and explain three basic data structures that are implemented in Dask.
  6. What is a Dask cluster?
  7. What do you have to do to tell TPOT it should use Dask for training?