Java for Data Science

Java for Data Science
Java for Data Science by Jennifer Reese, Richard Reese
English | 2017 | ISBN: 1785280115 | 558 Pages | True PDF, EPUB | 12 MB

Examine the techniques and Java tools supporting the growing field of data science
Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application.
The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation.
The final chapter illustrates an in-depth data science problem and provides a comprehensive, Java-based solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book.
What you will learn

  • Understand the nature and key concepts used in the field of data science
  • Grasp how data is collected, cleaned, and processed
  • Become comfortable with key data analysis techniques
  • See specialized analysis techniques centered on machine learning
  • Master the effective visualization of your data
  • Work with the Java APIs and techniques used to perform data analysis