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You're reading from Java for Data Science

Product typeBook

Published inJan 2017

Reading LevelIntermediate

PublisherPackt

ISBN-139781785280115

Edition1st Edition

Languages

Java

Tools

Weka Deeplearning4j

Concepts

Data Science

Authors (2):

Richard M. Reese

Jennifer L. Reese

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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.

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Java for Data Science

Published in: Jan 2017Publisher: PacktISBN-13: 9781785280115

Authors (2)

Richard M. Reese

Richard Reese has worked in the industry and academics for the past 29 years. For 10 years he provided software development support at Lockheed and at one point developed a C based network application. He was a contract instructor providing software training to industry for 5 years. Richard is currently an Associate Professor at Tarleton State University in Stephenville Texas. Richard is the author of various books and video courses some of which are as follows: Natural Language Processing with Java. Java for Data Science Getting Started with Natural Language Processing in Java
Read more about Richard M. Reese

Jennifer L. Reese

Jennifer L. Reese studied computer science at Tarleton State University. She also earned her M.Ed. from Tarleton in December 2016. She currently teaches computer science to high-school students. Her interests include the integration of computer science concepts with other academic disciplines, increasing diversity in computer science courses, and the application of data science to the field of education. She has co-authored two books: Java for Data Science and Java 7 New Features Cookbook. She previously worked as a software engineer. In her free time she enjoys reading, cooking, and traveling—especially to any destination with a beach. She is a musician and appreciates a variety of musical genres.
Read more about Jennifer L. Reese

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You're reading from Java for Data Science

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