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Mastering Java for Data Science

You're reading from   Mastering Java for Data Science Analytics and more for production-ready applications

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781782174271
Length 364 pages
Edition 1st Edition
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Author (1):
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Alexey Grigorev Alexey Grigorev
Author Profile Icon Alexey Grigorev
Alexey Grigorev
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Data Processing Toolbox

In the previous chapter, we discussed the best practices for approaching data science problems. We looked at CRISP-DM, which is the methodology for dealing with data mining projects, and one of the first steps there is data preprocessing. In this chapter, we will take a closer look at how to do this in Java.

Specifically, we will cover the following topics:

  • Standard Java library
  • Extensions to the standard library
  • Reading data from different sources such as text, HTML, JSON, and databases
  • DataFrames for manipulating tabular data

In the end, we will put everything together to prepare the data for the search engine.

By the end of this chapter, you will be able to process data such that it can be used for machine learning and further analysis.

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