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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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Summary

In this chapter, we briefly discussed data science and what role machine learning plays in it. Then we talked about doing a data science project, and what methodologies are useful for it. We discussed one of them, CRISP-DM, the steps it defines, how these steps are related and the outcome of each step.

Finally, we spoke about why doing a data science project in Java is a good idea, it is statically compiled, it's fast, and often the existing production systems already run in Java. We also mentioned libraries and frameworks one can use to successfully accomplish a data science project using the Java language.

With this foundation, we will now go to the most important (and most time-consuming) step in a data science project--Data Preparation.

You have been reading a chapter from
Mastering Java for Data Science
Published in: Apr 2017
Publisher: Packt
ISBN-13: 9781782174271
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