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Machine Learning with Spark. - Second Edition

You're reading from  Machine Learning with Spark. - Second Edition

Product type Book
Published in Apr 2017
Publisher Packt
ISBN-13 9781785889936
Pages 532 pages
Edition 2nd Edition
Languages
Authors (2):
Rajdeep Dua Rajdeep Dua
Profile icon Rajdeep Dua
Manpreet Singh Ghotra Manpreet Singh Ghotra
Profile icon Manpreet Singh Ghotra
View More author details
Toc

Table of Contents (13) Chapters close

Preface 1. Getting Up and Running with Spark 2. Math for Machine Learning 3. Designing a Machine Learning System 4. Obtaining, Processing, and Preparing Data with Spark 5. Building a Recommendation Engine with Spark 6. Building a Classification Model with Spark 7. Building a Regression Model with Spark 8. Building a Clustering Model with Spark 9. Dimensionality Reduction with Spark 10. Advanced Text Processing with Spark 11. Real-Time Machine Learning with Spark Streaming 12. Pipeline APIs for Spark ML

Obtaining, Processing, and Preparing Data with Spark

Machine learning is an extremely broad field, and these days, applications can be found across areas that include web and mobile applications, the Internet of Things and sensor networks, financial services, healthcare, and various scientific fields, to name just a few.

Therefore, the range of data available for potential use in machine learning is enormous. In this book, we will focus mostly on business applications. In this context, the data available often consists of data internal to an organization (such as transactional data for a financial services company) as well as external data sources (such as financial asset price data for the same financial services company).

For example, you'll recall from Chapter 3, Designing a Machine Learning System, that the main internal source of data for our hypothetical internet business, Movie Stream, consists of data...

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