Java for Data Science by Jennifer L. Reese

Key FeaturesYour entry ticket to the world of data science with the stability and power of JavaExplore, analyse, and visualize your data effectively using easy-to-follow examplesMake your Java applications more capable using machine learningBook DescriptionData 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 LearnUnderstand the nature and key concepts used in the field of data scienceGrasp how data is collected, cleaned, and processedBecome comfortable with key data analysis techniquesSee specialized analysis techniques centered on machine learningMaster the effective visualization of your dataWork with the Java APIs and techniques used to perform data analysisAbout the AuthorRichard M. Reese has worked in both industry and academics. For 17 years, he worked in the telephone and aerospace industries, serving in several capacities, including research and development, software development, supervision, and training. He currently teaches at Tarleton State University, where he has the opportunity to apply his years of industry experience to enhance his teaching.Richard has written several Java books and a C Pointer book. He uses a concise and easy-to-follow approach to topics at hand. His Java books have addressed EJB 3.1, updates to Java 7 and 8, certification, jMonkeyEngine, natural language processing, functional programming, and networks.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 research 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 previously worked as a software engineer developing software for county- and district-level government offices throughout Texas. 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.Table of ContentsGetting Started with Data ScienceData AcquisitionData CleaningData VisualizationStatistical Data Analysis TechniquesMachine LearningNeural NetworksDeep LearningText AnalysisVisual and Audio AnalysisMathematical and Parallel Techniques for Data AnalysisBringing It All Together