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Java: Data Science Made Easy
book

Java: Data Science Made Easy

by Richard M. Reese, Jennifer L. Reese, Alexey Grigorev
July 2017
Beginner to intermediate
715 pages
17h 3m
English
Packt Publishing
Content preview from Java: Data Science Made Easy

Mathematical and Parallel Techniques for Data Analysis

The concurrent execution of a program can result in significant performance improvements. In this chapter, we will address the various techniques that can be used in data science applications. These can range from low-level mathematical calculations to higher-level API-specific options.

Always keep in mind that performance enhancement starts with ensuring that the correct set of application functionality is implemented. If the application does not do what a user expects, then the enhancements are for nought. The architecture of the application and the algorithms used are also more important than code enhancements. Always use the most efficient algorithm. Code enhancement should then be ...

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Publisher Resources

ISBN: 9781788475655Supplemental Content