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Feature Engineering Made Easy

You're reading from   Feature Engineering Made Easy Identify unique features from your dataset in order to build powerful machine learning systems

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781787287600
Length 316 pages
Edition 1st Edition
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Authors (2):
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Divya Susarla Divya Susarla
Author Profile Icon Divya Susarla
Divya Susarla
Sinan Ozdemir Sinan Ozdemir
Author Profile Icon Sinan Ozdemir
Sinan Ozdemir
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Table of Contents (10) Chapters Close

Preface 1. Introduction to Feature Engineering 2. Feature Understanding – What's in My Dataset? FREE CHAPTER 3. Feature Improvement - Cleaning Datasets 4. Feature Construction 5. Feature Selection 6. Feature Transformations 7. Feature Learning 8. Case Studies 9. Other Books You May Enjoy

Summary

Understanding the features that we are working with is step zero of feature engineering. If we cannot understand the data given to us, we will never hope to fix, create, and utilize features in order to create well-performing, machine-learning pipelines. In this chapter, we were able to recognize, and extract the levels of data from our datasets and use that information to create useful and meaningful visuals that shine new lights on our data.

In the next chapter, we will use all of this new-found knowledge of the levels of data to start improving our features, and we will start to use machine-learning to effectively measure the impact of our feature engineering pipelines.

You have been reading a chapter from
Feature Engineering Made Easy
Published in: Jan 2018
Publisher: Packt
ISBN-13: 9781787287600
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