Examine the techniques and Java tools supporting the growing field of data science About This Book - Your entry ticket to the world of data science with the stability and power of Java - Explore, analyse, and visualize your data effectively using easy-to-follow examples - Make your Java applications more capable using machine learning Who This Book Is For This 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 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 In Detail 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. Style and approach This 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.

lgli/Packt - Java for Data Science 2017.pdf

lgrsnf/Packt - Java for Data Science 2017.pdf

zlib/Computers/Richard M. Reese, Jennifer L. Reese/Java for Data Science_2923945.pdf

Reese, Richard M., Reese, Jennifer L.

Richard M. Reese, Jennifer L. Reese

HarperCollins Publishers Ltd

Westermann Lernwelten GmbH

Packt Publishing Limited

Mills & Boon

Pavilion

United Kingdom and Ireland, United Kingdom

Birmingham, England, 2017

Germany, Germany

Jan 10, 2017

0

lg1681282

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<p>Examine the techniques and Java tools supporting the growing field of data science<br></p><p>About This Book<br></p><ul> <li>Your entry ticket to the world of data science with the stability and power of Java </li> <li>Explore, analyse, and visualize your data effectively using easy-to-follow examples </li> <li>Make your Java applications more capable using machine learning </li></ul><p>Who This Book Is For<br></p><p>This 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.<br></p><p>What You Will Learn<br></p><ul> <li>Understand the nature and key concepts used in the field of data science </li> <li>Grasp how data is collected, cleaned, and processed </li> <li>Become comfortable with key data analysis techniques </li> <li>See specialized analysis techniques centered on machine learning </li> <li>Master the effective visualization of your data </li> <li>Work with the Java APIs and techniques used to perform data analysis </li></ul><p>In Detail<br></p><p>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.<br></p><p>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.<br></p><p>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.<br></p><p>Style and approach<br></p><p>This book follows a tutorial approach, providing examples of each of the major concepts covered.<br></p><p>With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.<br></p>

Annotation Examine the techniques and Java tools supporting the growing field of data scienceAbout This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples Make 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 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 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

About 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 of 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 analysisGet to grips with AI techniques for performing tasks such as pattern recognition and information derivationIn DetailData science draws from a wide array of disciplines, including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the major data science concepts and demonstrate how they are supported by Java, as well as examine statistical techniques, to provide you with an understanding of their purpose and application.The book starts with an introduction to 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.

2017-04-26