Data Science with Java

Practical Methods for Scientists and Engineers

Nonfiction, Computers, Internet, Web Development, Java, Programming, Programming Languages
Cover of the book Data Science with Java by Michael R. Brzustowicz, PhD, O'Reilly Media
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Author: Michael R. Brzustowicz, PhD ISBN: 9781491934067
Publisher: O'Reilly Media Publication: June 6, 2017
Imprint: O'Reilly Media Language: English
Author: Michael R. Brzustowicz, PhD
ISBN: 9781491934067
Publisher: O'Reilly Media
Publication: June 6, 2017
Imprint: O'Reilly Media
Language: English

Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today’s data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java.

You’ll learn the critical roles that data IO, linear algebra, statistics, data operations, learning and prediction, and Hadoop MapReduce play in the process. Throughout this book, you’ll find code examples you can use in your applications.

  • Examine methods for obtaining, cleaning, and arranging data into its purest form
  • Understand the matrix structure that your data should take
  • Learn basic concepts for testing the origin and validity of data
  • Transform your data into stable and usable numerical values
  • Understand supervised and unsupervised learning algorithms, and methods for evaluating their success
  • Get up and running with MapReduce, using customized components suitable for data science algorithms
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today’s data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java.

You’ll learn the critical roles that data IO, linear algebra, statistics, data operations, learning and prediction, and Hadoop MapReduce play in the process. Throughout this book, you’ll find code examples you can use in your applications.

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