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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
Transitioning from Data Developer to Data Scientist Declaring the Objectives A Developer's Approach to Data Cleaning Data Mining and the Database Developer Statistical Analysis for the Database Developer Database Progression to Database Regression Regularization for Database Improvement Database Development and Assessment Databases and Neural Networks Boosting your Database Database Classification using Support Vector Machines Database Structures and Machine Learning

Summary


In this chapter, we discovered statistical boosting, first providing an explanation of the key concepts used in statistics relevant to the topic of boosting, thus helping to define boosting itself.

We also contemplated the notion of using statistical boosting to better understand data in just about every database.

In the next chapter, will again strive to use developer terminologies, this time in an effort to define a support vector machine, identify various applications for its use, and walk through an example of using a simple SVM to classify the data in a database.

 

 

 

 

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