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Apache Spark Machine Learning Blueprints

You're reading from   Apache Spark Machine Learning Blueprints Develop a range of cutting-edge machine learning projects with Apache Spark using this actionable guide

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Product type Paperback
Published in May 2016
Publisher Packt
ISBN-13 9781785880391
Length 252 pages
Edition 1st Edition
Languages
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Author (1):
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Alex Liu Alex Liu
Author Profile Icon Alex Liu
Alex Liu
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Table of Contents (13) Chapters Close

Preface 1. Spark for Machine Learning FREE CHAPTER 2. Data Preparation for Spark ML 3. A Holistic View on Spark 4. Fraud Detection on Spark 5. Risk Scoring on Spark 6. Churn Prediction on Spark 7. Recommendations on Spark 8. Learning Analytics on Spark 9. City Analytics on Spark 10. Learning Telco Data on Spark 11. Modeling Open Data on Spark Index

Deployment


In the past, rankings were mostly reviewed as a reference by users. With this project, we found we are also in a position to assist our users in integrating our results with their decision-making tools, to help them utilize rankings better and also make their lives easier. For this, producing rules from rankings and also making scores behind rankings easily accessible became very important.

Because of the preceding reason, our deployment is still on to develop a set of rules and also to make all the scores available for decision makers, which include schools and some parents. Specifically, the main task of sending out a rule to alert users when some ranking changes dramatically, especially when a ranking drops down dramatically. Users of this project also have a need to obtain all the scores and rankings for their management performance.

Another purpose for this project is to produce good predictive models for the users to forecast possible changes of school rankings as per population...

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