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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 2. Introduction to Machine Learning Using Python FREE CHAPTER 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

The phases of an engagement model

A very well-known modeling process is CRISP-DM for data mining and predictive analytics projects, and it involves six steps:

  1. Business understanding
  2. Data understanding
  3. Data preparation
  4. Modeling
  5. Evaluation
  6. Deployment

Each of these phases follows each other, and some of them happen in a recursive fashion by providing feedback to the preceding phase. The deployment phase is particularly important in terms of model monitoring and maintenance, which is the focus of this chapter.

Let's quickly look at each of these phases and their purpose in the overall process.

Business understanding

This is the phase where you fully focus on the business objectives in terms of project goals, scope, resources...

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