Java for Data Science (eBook)

Examine the techniques and Java tools supporting the growing field of data science

Richard M. Reese, Jennifer L. Reese (Autoren)

eBook Download: EPUB

2017
386 Seiten
Packt Publishing (Verlag)
978-1-78528-124-2 (ISBN)

Infos

para 1: Get the lowdown on Java and explore big data analytics with Java for Data Science. Packed with examples and data science principles, this book uncovers the techniques & Java tools supporting data science and machine learning. Para 2: The stability and power of Java combines with key data science concepts for effective exploration of data. By working with Java APIs and techniques, this data science book allows you to build applications and use analysis techniques centred on machine learning. Para 3: Java for Data Science gives you the understanding you need to examine the techniques and Java tools supporting big data analytics. These Java-based approaches allow you to tackle data mining and statistical analysis in detail. Deep learning and Java data mining are also featured, so you can explore and analyse data effectively, and build intelligent applications using machine learning. para 4: What?s Inside ? Understand data science principles with Java support ? Discover machine learning and deep learning essentials ? Explore data science problems with Java-based solutions

---

Examine the techniques and Java tools supporting the growing field of data scienceAbout This BookYour 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 learningWho This Book Is ForThis book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful.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 analysisIn DetailData 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.Style and approachThis book follows a tutorial approach, providing examples of each of the major concepts covered.With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.

Produkt-Details

• Erscheint lt. Verlag: 10.1.2017
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Mathematik / Informatik ► Informatik ► Web / Internet
• ISBN-10: 1-78528-124-0 / 1785281240
• ISBN-13: 978-1-78528-124-2 / 9781785281242