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Statistics for Data Science

You're reading from  Statistics for Data Science

Product type Book
Published in Nov 2017
Publisher Packt
ISBN-13 9781788290678
Pages 286 pages
Edition 1st Edition
Languages
Concepts

Table of Contents (19) Chapters

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Transitioning from Data Developer to Data Scientist 2. Declaring the Objectives 3. A Developer's Approach to Data Cleaning 4. Data Mining and the Database Developer 5. Statistical Analysis for the Database Developer 6. Database Progression to Database Regression 7. Regularization for Database Improvement 8. Database Development and Assessment 9. Databases and Neural Networks 10. Boosting your Database 11. Database Classification using Support Vector Machines 12. Database Structures and Machine Learning

Chapter 2. Declaring the Objectives

This chapter introduces and explains (yet again, from a developer's perspective) the basic objectives behind statistics for data science and introduces the reader to the important terms and key concepts (with explanations and examples) that are used throughout the book.

In this chapter, we've broken things down into the following topics:

  • A primer on the key objectives of data science
  • Bringing statistics into data science
  • Common terminologies used with statistics and data science
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