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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

Table of Contents (13) Chapters

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

The components of a data-driven machine learning system

The high-level components of our machine learning system are outlined in the following diagram. This diagram illustrates the machine learning pipeline from which we obtain data and in which we store data. We then transform it into a form that is usable as input to a machine learning model; train, test, and refine our model; and then, deploy the final model to our production system. The process is then repeated as new data is generated.

A general machine-learning pipeline

Data ingestion and storage

The first step in our machine learning pipeline will be taking in the data that we require for training our models. Like many other businesses, MovieStream's data is typically generated by user activity, other...

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