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Machine Learning with Spark

You're reading from   Machine Learning with Spark Develop intelligent, distributed machine learning systems

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781785889936
Length 532 pages
Edition 2nd Edition
Languages
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Authors (2):
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Manpreet Singh Ghotra Manpreet Singh Ghotra
Author Profile Icon Manpreet Singh Ghotra
Manpreet Singh Ghotra
Rajdeep Dua Rajdeep Dua
Author Profile Icon Rajdeep Dua
Rajdeep Dua
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Up and Running with Spark FREE CHAPTER 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

Introducing MovieStream

To better illustrate the design of our architecture, we will introduce a practical scenario. Let's assume that we have just been appointed to head the data science team of MovieStream, a fictitious Internet business that streams movies and television shows to its users.

MovieStream system is outlined in the following diagram:

MovieStream's current architecture

As we can see in the preceding diagram, currently, MovieStream's content editorial team is responsible for deciding which movies and shows are promoted and shown in various parts of the site. They are also responsible for creating the content for MovieStream's bulk marketing campaigns, which include e-mail and other direct marketing channels. Currently, MovieStream collects basic data on what titles are viewed by users on an aggregate basis and has access to some demographic data collected from users when they sign...

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