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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide - Second Edition

You're reading from  AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide - Second Edition

Product type Book
Published in Feb 2024
Publisher Packt
ISBN-13 9781835082201
Pages 342 pages
Edition 2nd Edition
Languages
Authors (2):
Somanath Nanda Somanath Nanda
Profile icon Somanath Nanda
Weslley Moura Weslley Moura
Profile icon Weslley Moura
View More author details

Table of Contents (13) Chapters

Preface 1. Chapter 1: Machine Learning Fundamentals 2. Chapter 2: AWS Services for Data Storage 3. Chapter 3: AWS Services for Data Migration and Processing 4. Chapter 4: Data Preparation and Transformation 5. Chapter 5: Data Understanding and Visualization 6. Chapter 6: Applying Machine Learning Algorithms 7. Chapter 7: Evaluating and Optimizing Models 8. Chapter 8: AWS Application Services for AI/ML 9. Chapter 9: Amazon SageMaker Modeling 10. Chapter 10: Model Deployment 11. Chapter 11: Accessing the Online Practice Resources 12. Other Books You May Enjoy

Dealing with categorical features

Data transformation methods for categorical features will vary according to the sub-type of your variable. In the upcoming sections, you will understand how to transform nominal and ordinal features.

Transforming nominal features

You may have to create numerical representations of your categorical features before applying ML algorithms to them. Some libraries may have embedded logic to handle that transformation for you, but most of them do not.

The first transformation you will learn is known as label encoding. A label encoder is suitable for categorical/nominal variables, and it will just associate a number with each distinct label of your variables. Table 4.2 shows how a label encoder works:

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Country

Label encoding

India

1

Canada

2

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