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Practical Predictive Analytics

You're reading from   Practical Predictive Analytics Analyse current and historical data to predict future trends using R, Spark, and more

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781785886188
Length 576 pages
Edition 1st Edition
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Author (1):
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Ralph Winters Ralph Winters
Author Profile Icon Ralph Winters
Ralph Winters
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with Predictive Analytics FREE CHAPTER 2. The Modeling Process 3. Inputting and Exploring Data 4. Introduction to Regression Algorithms 5. Introduction to Decision Trees, Clustering, and SVM 6. Using Survival Analysis to Predict and Analyze Customer Churn 7. Using Market Basket Analysis as a Recommender Engine 8. Exploring Health Care Enrollment Data as a Time Series 9. Introduction to Spark Using R 10. Exploring Large Datasets Using Spark 11. Spark Machine Learning - Regression and Cluster Models 12. Spark Models – Rule-Based Learning

Importing the sample notebook

The best way to run the examples in this chapter is by importing the notebook from an external site. To do this:

  1. Click on Workspace.
  2. Right-click on Training & Tutorials (or an alternate folder) and select Import.
  3. Drag the file downloaded from the publisher site into the drop area and click on Import.

See the following screenshot:

After you import your notebook, all of the code and output will appear and you will be free to follow along with the remaining code examples.

Notebook format

Databricks notebooks contain the written code in the cell in the upper pane, followed by any output in the lower cell, similar to the tutorial code for the 'diamonds' data which is displayed next...

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