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Java: Data Science Made Easy

You're reading from   Java: Data Science Made Easy Data collection, processing, analysis, and more

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Product type Course
Published in Jul 2017
Publisher Packt
ISBN-13 9781788475655
Length 734 pages
Edition 1st Edition
Languages
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Authors (3):
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Alexey Grigorev Alexey Grigorev
Author Profile Icon Alexey Grigorev
Alexey Grigorev
Richard M. Reese Richard M. Reese
Author Profile Icon Richard M. Reese
Richard M. Reese
Jennifer L. Reese Jennifer L. Reese
Author Profile Icon Jennifer L. Reese
Jennifer L. Reese
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Toc

Table of Contents (29) Chapters Close

Title Page
Credits
Preface
1. Module 1 FREE CHAPTER
2. Getting Started with Data Science 3. Data Acquisition 4. Data Cleaning 5. Data Visualization 6. Statistical Data Analysis Techniques 7. Machine Learning 8. Neural Networks 9. Deep Learning 10. Text Analysis 11. Visual and Audio Analysis 12. Visual and Audio Analysis 13. Mathematical and Parallel Techniques for Data Analysis 14. Bringing It All Together 15. Module 2
16. Data Science Using Java 17. Data Processing Toolbox 18. Exploratory Data Analysis 19. Supervised Learning - Classification and Regression 20. Unsupervised Learning - Clustering and Dimensionality Reduction 21. Working with Text - Natural Language Processing and Information Retrieval 22. Extreme Gradient Boosting 23. Deep Learning with DeepLearning4J 24. Scaling Data Science 25. Deploying Data Science Models 26. Bibliography

Interactive Exploratory Data Analysis in Java


Java is a statically typed programming language and code written in Java needs compiling. While Java is good for developing complex data science applications, it makes it harder to interactively explore the data; every time, we need to recompile the source code and re-run the analysis script to see the results. This means that, if we need to read some data, we will have to do it over and over again. If the dataset is large, the program takes more time to start.

So it is hard to interact with data and this makes EDA more difficult in Java than in other languages. In particular, Read-Evaluate-Print Loop (REPL), an interactive shell, is quite an important feature for doing EDA.

Unfortunately, Java 8 does not have REPL, but there are several alternatives:

  • Other interactive JVM languages such as JavaScript, Groovy, or Scala
  • Java 9 with jshell
  • Completely alternative platforms such as Python or R

In this chapter, we will look at the first two options--JVM...

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