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Java for Data Science

You're reading from   Java for Data Science Examine the techniques and Java tools supporting the growing field of data science

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Product type Paperback
Published in Jan 2017
Publisher Packt
ISBN-13 9781785280115
Length 386 pages
Edition 1st Edition
Languages
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Authors (2):
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Jennifer L. Reese Jennifer L. Reese
Author Profile Icon Jennifer L. Reese
Jennifer L. Reese
Richard M. Reese Richard M. Reese
Author Profile Icon Richard M. Reese
Richard M. Reese
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with Data Science 2. Data Acquisition FREE CHAPTER 3. Data Cleaning 4. Data Visualization 5. Statistical Data Analysis Techniques 6. Machine Learning 7. Neural Networks 8. Deep Learning 9. Text Analysis 10. Visual and Audio Analysis 11. Mathematical and Parallel Techniques for Data Analysis 12. Bringing It All Together

Summary


In this chapter, we discussed types of data that are useful for data science and readily accessible on the Internet. This discussion included details about file specifications and formats for the most common types of data sources.

We also examined Java APIs and other techniques for retrieving data, and illustrated this process with multiple sources. In particular, we focused on types of text-based document formats and multimedia files. We used web crawlers to access websites and then performed web scraping to retrieve data from the sites we encountered.

Finally, we extracted data from social media sites and examined the available Java support. We retrieved data from Twitter, Wikipedia, Flickr, and YouTube and examined the available API support.

You have been reading a chapter from
Java for Data Science
Published in: Jan 2017
Publisher: Packt
ISBN-13: 9781785280115
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