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Hands-On Automated Machine Learning

You're reading from   Hands-On Automated Machine Learning A beginner's guide to building automated machine learning systems using AutoML and Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788629898
Length 282 pages
Edition 1st Edition
Languages
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Authors (2):
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Umit Mert Cakmak Umit Mert Cakmak
Author Profile Icon Umit Mert Cakmak
Umit Mert Cakmak
Sibanjan Das Sibanjan Das
Author Profile Icon Sibanjan Das
Sibanjan Das
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to AutoML FREE CHAPTER 2. Introduction to Machine Learning Using Python 3. Data Preprocessing 4. Automated Algorithm Selection 5. Hyperparameter Optimization 6. Creating AutoML Pipelines 7. Dive into Deep Learning 8. Critical Aspects of ML and Data Science Projects 9. Other Books You May Enjoy

Critical Aspects of ML and Data Science Projects

If you have made it this far, give yourself a pat on the shoulder. This is not to think of yourself as a machine learning (ML) expert, but rather to acknowledge the work that you have done to learn Automated ML (AutoML) workflows. You are now ready to apply these techniques to solve your problems!

In this chapter, you are going to review what you have learned throughout the chapters and put your learning into a broader perspective.

We will be covering the following topics in our discussion:

  • Machine learning as a search
  • Trade-offs in ML
  • An engagement model for a typical data science project
  • The phases of an engagement model
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