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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

Introduction to Machine Learning Using Python

The last chapter introduced you to the world of machine learning (ML). In this chapter, we will develop the ML foundations that are required for building and using Automated ML (AutoML) platforms. It is not always clear how ML is best applied or what it takes to implement it. However, ML tools are getting more straightforward to use, and AutoML platforms are making it more accessible to a broader audience. In the future there will undoubtedly be a higher collaboration between man and machine.

The future of ML may require people to prepare data for its consumption and identify use cases for implementation. More importantly, people are needed to interpret the results and audit the ML system—whether they are following the right and best approaches to solving a problem. The future looks pretty amazing, but we need to build that...

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