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Learning Apache Spark 2

You're reading from   Learning Apache Spark 2 A beginner's guide to real-time Big Data processing using the Apache Spark framework

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781785885136
Length 356 pages
Edition 1st Edition
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Author (1):
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Muhammad Asif Abbasi Muhammad Asif Abbasi
Author Profile Icon Muhammad Asif Abbasi
Muhammad Asif Abbasi
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Table of Contents (12) Chapters Close

Preface 1. Architecture and Installation 2. Transformations and Actions with Spark RDDs FREE CHAPTER 3. ETL with Spark 4. Spark SQL 5. Spark Streaming 6. Machine Learning with Spark 7. GraphX 8. Operating in Clustered Mode 9. Building a Recommendation System 10. Customer Churn Prediction Theres More with Spark

Types of machine learning


There are four major categories of machine learning algorithms:

  • Supervised learning: In supervised learning, we have a bunch of data that has already been labeled, and can be used to train a model, which can later be used to predict the labels of new and un-labeled data. A simple example could be data on a list of customers who have previously churned, or people who have defaulted on their loans. We can use this data to train a model, and understand the behaviors demonstrated by churners or loan-defaulters. Once we have trained a model, we can use this model to detect churners or loan-defaulters by looking at similar attributes, and identifying the likelihood of a person being a churner or a loan defaulter. This is also sometimes known as predictive modeling or predictive analytic. Example algorithms include:

    • Decision trees
    • Regression
    • Neural networks
    • SVM

    Figure 6.3: Supervised learning

  • Unsupervised learning: In unsupervised learning, there is no pre-existing data with...

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