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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

Data acquisition techniques


In this section, we will illustrate how to acquire data from web pages. Web pages contain a potential bounty of useful information. We will demonstrate how to access web pages using several technologies, starting with a low-level approach supported by the HttpUrlConnection class. To find pages, a web crawler application is often used. Once a useful page has been identified, then information needs to be extracted from the page. This is often performed using an HTML parser. Extracting this information is important because it is often buried amid a clutter of HTML tags and JavaScript code.

Using the HttpUrlConnection class

The contents of a web page can be accessed using the HttpUrlConnection class. This is a low-level approach that requires the developer to do a lot of footwork to extract relevant content. However, he or she is able to exercise greater control over how the content is handled. In some situations, this approach may be preferable to using other API libraries...

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