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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

An architecture for a machine learning system

Now that we have explored how our machine learning system might work in the context of MovieStream, we can outline a possible architecture for our system:

MovieStream's future architecture

As we can see, our system incorporates the machine learning pipeline outlined in the preceding diagram; this system also includes:

  • Collecting data about users, their behavior, and our content titles
  • Transforming this data into features
  • Training our models, including our training-testing and model-selection phases
  • Deploying the trained models to both our live model-serving system as well as using these models for offline processes
  • Feeding back the model results into the MovieStream website through recommendation and targeting pages
  • Feeding back the model results into MovieStream's personalized marketing channels
  • Using the offline models to provide tools to MovieStream&apos...
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