Data Science with Java: Practical Methods for Scientists and Engineers 1st Edition

Data Science is booming thanks to R Python and, 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 IO data, 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 чисельного values
• Understand supervised unsupervised learning and algorithms, and methods for evaluating their success
• Get up and running with MapReduce, using customized components suitable for data science algorithms