Scientific data analysis using jython scripting and java

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Scientific Data Analysis using Jython Scripting and Java

Scientific Data Analysis using Jython Scripting and Java @ eBooks.com

USD 99.00
Written by the primary developer of the jHepWork data analysis framework, this practical book, complete with dozens of code snippets, is a reliable reference source that enables readers to lay the foundation for data-analysis applications using Java scripting.
Jython Essentials

Jython Essentials @ eBooks.com

USD 27.99
Jython is an implementation of the Python programming language written in 100% pure Java, so it runs under any compliant Java Virtual Machine. The secret to Jython's popularity lies in the combination of Java's librariesand tools with Python's rapid development capabilities. With Jython, you can write Python programs that integrate seamlessly with any Java code. And like Python, Jython can be used interactively, so you can get immediate results as you are programming. Jython Essentials provides a solid introduction to the Python language, offering a brief but thorough tour of the Python concepts you'll need to understand to use Jython effectively. The book makes frequent comparisonsbetween Python and Java, with special emphasis on the different object-oriented semantics of the two languages, so Java programmers can quickly get up to speed with Jython. Jython Essentials also covers the various ways in which Jython and Java can interact. For example, Jython code can create instances of pre-existing Java classes and call methods in those instances. You can write Jython classes that are direct subclasses of existing Java classesand use introspection to discern the capabilities of JavaBeans components. This book provides examples of using Jython with existing Java libraries, including the Swing GUI toolkit, the JDBC database API, the Servlet API, and various XML tools. And finally, the book shows howJython can be used as a scripting language within a Java program.With Jython Essentials , you have everything you need to start creating applications that mix the best of Python's interactivity and Java's robust libraries.
Numeric Computation and Statistical Data Analysis on the Java Platform

Numeric Computation and Statistical Data Analysis on the Java Platform @ eBooks.com

USD 99.00
Numericalcomputation, knowledge discovery and statistical data analysis integrated withpowerful 2D and 3D graphics for visualization are the key topics of this book. ThePython code examples powered by the Java platform can easily be transformed toother programming languages, such as Java, Groovy, Ruby and BeanShell. Thisbook equips the reader with acomputational platform which, unlike other statistical programs, is not limitedby a single programming language. The authorfocuses on practical programming aspects and covers a broad range of topics,from basic introduction to the Python language on the Java platform (Jython),to descriptive statistics, symbolic calculations, neural networks, non-linearregression analysis and many other data-mining topics. He discusses how to findregularities in real-world data, how to classify data, and how to process datafor knowledge discoveries. The code snippets are so short that they easily fit intosingle pages. Numeric Computation and Statistical DataAnalysis on the Java Platform is a great choice for those who want to learn how statisticaldata analysis can be done using popular programming languages, who want tointegrate data analysis algorithms in full-scale applications, and deploy suchcalculations on the web pages or computational servers regardless of their operating system. It is an excellent reference for scientific computations to solvereal-world problems using a comprehensive stack of open-source Javalibraries included in the DataMelt (DMelt) project and will beappreciated by many data-analysis scientists, engineers and students .
Scripting in Java

Scripting in Java @ eBooks.com

USD 34.99
Scripting in Java teaches you how to use the Java Scripting API and JavaScript to execute scripts and take advantage of the features of a scripting language while developing Java applications. The book also covers topics that enable scripting languages to take advantage of Java features and the Java class library, including the new Java Collections and JavaFX 8 APIs. Most of the examples in this book use JavaScript on the Nashorn engine. Author Kishori Sharan will show you scripts in JavaScript to demonstrate its power and use in your Java applications. Some of the examples use the jrunscript and jjs command-line tools. Furthermore, debugging is discussed to equip you for situations when or if you encounter any issues with this kind of Java scripting. After reading and using this book, you will have most of what you need to do scripting in Java.
Scripting in Java

Scripting in Java @ eBooks.com

USD 47.99
This is the eBook version of the printed book. If the print book includes a CD-ROM, this content is not included within the eBook version. Groovy and Beyond: Leverage the Full Power of Scripting on the Java TM Platform! Using the Java TM platform's new scripting support, you can improve efficiency, streamline your development processes, and solve problems ranging from prototyping to Web application programming. In Scripting in Java , Dejan Bosanac covers key aspects of scripting with Java, from the exciting new Groovy scripting language to Java's new Scripting and Web Scripting APIs. Bosanac begins by reviewing the role and value of scripting languages, and then systematically introduces today's best scripting solutions for the Java platform. He introduces Java scripting frameworks, identifies proven patterns for integrating scripting into Java applications, and presents practical techniques for everything from unit testing to project builds. He supports key concepts with extensive code examples that demonstrate scripting at work in real-world Java projects. Coverage includes Why scripting languages offer surprising value to Java programmers Scripting languages that run inside the JVM: BeanShell, JavaScript, and Python Groovy in depth: installation, configuration, Java-like syntax, Java integration, security, and more Groovy extensions: accessing databases, working with XML, and building simple Web applications and Swing-based UIs Bean Scripting Framework: implementation, basic abstractions, and usage examples Traditional and new patterns for Java-based scripting JSR 223 Scripting API: language bindings, discovery mechanisms, threading, pluggable namespaces, and more JSR 223 Web Scripting Framework: scripting the generation of Web content within servlet containers About the Web Site All code examples are available for download at this book's companion Web site.
Automated Data Analysis Using Excel

Automated Data Analysis Using Excel @ eBooks.com

USD 79.95
Because the analysis of copious amounts of data and the preparation of custom reports often take away time from true research, the automation of these processes is paramount to ensure productivity. Exploring the core areas of automation, report generation, data acquisition, and data analysis, Automated Data Analysis Using Excel illustrates how to minimize user intervention, automate parameter setup, obtain consistency in both analysis and reporting, and save time through automation. Focusing on the built-in Visual Basic for Applications (VBA) scripting language of Excel, the book shows step-by-step how to construct useful automated data analysis applications for both industrial and academic settings. It begins by discussing fundamental elements, the methods for importing and accessing data, and the creation of reports. The author then describes how to use Excel to obtain data from non-native sources, such as databases and third-party calculation tools. After providing the means to access any required information, the book explains how to automate manipulations and calculations on the acquired data sources. Collecting all of the concepts previously discussed in the book, the final chapter demonstrates from beginning to end how to create a cohesive, robust application. With an understanding of this book, readers should be able to construct applications that can import data from a variety of sources, apply algorithms to data that has been imported, and create meaningful reports based on the results.
Introduction to Scientific Computing and Data Analysis

Introduction to Scientific Computing and Data Analysis @ eBooks.com

USD 79.99
This textbook provides and introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimization and regression based methods using a singular value decomposition. The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used. The MATLAB codes used to produce most of the figures and data tables in the text are available on the author's website and SpringerLink.
Java for Data Science

Java for Data Science @ eBooks.com

USD 39.99
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.
Data Analysis Using SAS

Data Analysis Using SAS @ eBooks.com

USD 105.00
This book provides students with a hands-on, exercise-heavy method for learning basic to intermediate SAS commands while understanding how to apply statistics and reasoning to real-world problems.
A Practical Guide to Data Structures and Algorithms using Java

A Practical Guide to Data Structures and Algorithms using Java @ eBooks.com

USD 115.95
Although traditional texts present isolated algorithms and data structures, they do not provide a unifying structure and offer little guidance on how to appropriately select among them. Furthermore, these texts furnish little, if any, source code and leave many of the more difficult aspects of the implementation as exercises. A fresh alternative to conventional data structures and algorithms books, A Practical Guide to Data Structures and Algorithms using Java presents comprehensive coverage of fundamental data structures and algorithms in a unifying framework with full implementation details. Recognizing that software development is a top-down process, this applications-centered book provides careful guidance to students and practitioners. Complete and thoroughly integrated Java implementations expose key differences among a wide range of important data structures, including many useful abstract data types not provided in standard Java libraries. Fundamental algorithms appear within the context of their supporting data structures. Case studies, examples, decision trees, and comparison charts throughout the stylized presentation illustrate and support an efficient methodology for the careful selection and application of data structures and algorithms. Appendices summarize major features of the Java programming language, introduce asymptotic notation and complexity analysis, and discuss design patterns applied in the book. A true marriage of theory and practice, this book sets a new standard as a comprehensive practical guide to data structures and algorithms. Practitioners and students will reach for this book often to quickly identify the best data structure or algorithm for their applications.