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Author: John Ferguson Smart
Publisher: "O'Reilly Media, Inc."
ISBN: 0596527934
Category : Computers
Languages : en
Pages : 910
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Book Description
This comprehensive work delivers 30 Open Source tools designed to improve the development practices of Java developers in any size team or organization.
Author: John Ferguson Smart
Publisher: "O'Reilly Media, Inc."
ISBN: 0596527934
Category : Computers
Languages : en
Pages : 910
Get Book Here
Book Description
This comprehensive work delivers 30 Open Source tools designed to improve the development practices of Java developers in any size team or organization.
Author: John Ferguson Smart
Publisher: "O'Reilly Media, Inc."
ISBN: 149195454X
Category : Computers
Languages : en
Pages : 910
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Book Description
All true craftsmen need the best tools to do their finest work, and programmers are no different. Java Power Tools delivers 30 open source tools designed to improve the development practices of Java developers in any size team or organization. Each chapter includes a series of short articles about one particular tool -- whether it's for build systems, version control, or other aspects of the development process -- giving you the equivalent of 30 short reference books in one package. No matter which development method your team chooses, whether it's Agile, RUP, XP, SCRUM, or one of many others available, Java Power Tools provides practical techniques and tools to help you optimize the process. The book discusses key Java development problem areas and best practices, and focuses on open source tools that can help increase productivity in each area of the development cycle, including: Build tools including Ant and Maven 2 Version control tools such as CVS and Subversion, the two most prominent open source tools Quality metrics tools that measure different aspects of code quality, including CheckStyle, PMD, FindBugs and Jupiter Technical documentation tools that can help you generate good technical documentation without spending too much effort writing and maintaining it Unit Testing tools including JUnit 4, TestNG, and the open source coverage tool Cobertura Integration, Load and Performance Testing to integrate performance tests into unit tests, load-test your application, and automatically test web services, Swing interfaces and web interfaces Issue management tools including Bugzilla and Trac Continuous Integration tools such as Continuum, Cruise Control, LuntBuild and Hudson If you are a Java developer, these tools can help improve your development practices, and make your life easier in the process. Lead developers, software architects and people interested in the wider picture will be able to gather from these pages some useful ideas about improving your project infrastructure and best practices.
Author: Ian H. Witten
Publisher: Elsevier
ISBN: 0080890369
Category : Computers
Languages : en
Pages : 665
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Book Description
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. - Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects - Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods - Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization
Author: James Avery
Publisher: "O'Reilly Media, Inc."
ISBN: 0596527543
Category : Computers
Languages : en
Pages : 1308
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Book Description
A wealth of open and free software is available today for Windows developers who want to extend the development environment, reduce development effort, and increase productivity. This encyclopedic guide explores more than 100 free and open source tools available to programmers who build applications for Windows desktops and servers.
Author: Yusuke Sugomori
Publisher: Packt Publishing Ltd
ISBN: 1785283146
Category : Computers
Languages : en
Pages : 254
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Book Description
Dive into the future of data science and learn how to build the sophisticated algorithms that are fundamental to deep learning and AI with Java About This Book Go beyond the theory and put Deep Learning into practice with Java Find out how to build a range of Deep Learning algorithms using a range of leading frameworks including DL4J, Theano and Caffe Whether you're a data scientist or Java developer, dive in and find out how to tackle Deep Learning Who This Book Is For This book is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It would also be good for machine learning users who intend to leverage deep learning in their projects, working within a big data environment. What You Will Learn Get a practical deep dive into machine learning and deep learning algorithms Implement machine learning algorithms related to deep learning Explore neural networks using some of the most popular Deep Learning frameworks Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms Discover more deep learning algorithms with Dropout and Convolutional Neural Networks Gain an insight into the deep learning library DL4J and its practical uses Get to know device strategies to use deep learning algorithms and libraries in the real world Explore deep learning further with Theano and Caffe In Detail AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Deep Learning algorithms are being used across a broad range of industries – as the fundamental driver of AI, being able to tackle Deep Learning is going to a vital and valuable skill not only within the tech world but also for the wider global economy that depends upon knowledge and insight for growth and success. It's something that's moving beyond the realm of data science – if you're a Java developer, this book gives you a great opportunity to expand your skillset. Starting with an introduction to basic machine learning algorithms, to give you a solid foundation, Deep Learning with Java takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. Once you've got to grips with the fundamental mathematical principles, you'll start exploring neural networks and identify how to tackle challenges in large networks using advanced algorithms. You will learn how to use the DL4J library and apply Deep Learning to a range of real-world use cases. Featuring further guidance and insights to help you solve challenging problems in image processing, speech recognition, language modeling, this book will make you rethink what you can do with Java, showing you how to use it for truly cutting-edge predictive insights. As a bonus, you'll also be able to get to grips with Theano and Caffe, two of the most important tools in Deep Learning today. By the end of the book, you'll be ready to tackle Deep Learning with Java. Wherever you've come from – whether you're a data scientist or Java developer – you will become a part of the Deep Learning revolution! Style and approach This is a step-by-step, practical tutorial that discusses key concepts. This book offers a hands-on approach to key algorithms to help you develop a greater understanding of deep learning. It is packed with implementations from scratch, with detailed explanation that make the concepts easy to understand and follow.
Author: Chris Tyler
Publisher: "O'Reilly Media, Inc."
ISBN: 0596101953
Category : Computers
Languages : en
Pages : 273
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Book Description
Provides information on the X Window System, covering such topics as X.org configuration, the X Server, utility programs, remote access, VNC, and keyboard configuration.
Author: Dean Wampler
Publisher: "O'Reilly Media, Inc."
ISBN: 1449311032
Category : Computers
Languages : en
Pages : 89
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Book Description
"Dean Wampler, Java expert and author of Programmin Scala (O'Reilley), shows you how to apply principles such as immutability, avoidance of side effects, and higher-order functions to your Java code. Each chapter provides exercises to help you practice what you've learned. Once you grasp the benefits of functional programming, you'll discover that it improves all the code you write."--From p. [4] of cover.
Author: Richard Hightower
Publisher: John Wiley & Sons
ISBN: 0764556177
Category : Computers
Languages : en
Pages : 769
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Book Description
What is this book about? The Extreme Programming (XP) methodology enables you to build and test enterprise systems quickly without sacrificing quality. In the last few years, open source developers have created or significantly improved a host of Java XP tools, from XDoclet, Maven, AntHill, and Eclipse to Ant, JUnit, and Cactus. This practical, code-intensive guide shows you how to put these tools to work — and capitalize on the benefits of Extreme Programming. Using an example pet store application, our expert Java developers demonstrate how to harness the latest versions of Ant and XDoclet for automated building and continuous integration. They then explain how to automate the testing process using JUnit, Cactus, and other tools, and to enhance project management and continuous integration through Maven and AntHill. Finally, they show you how to work with XP tools in the new Eclipse IDE. Complete with real-world advice on how to implement the principles and practices of effective developers, this book delivers everything you need to harness the power of Extreme Programming in your own projects. What does this book cover? Here are some of the things you'll find out about in this book: How to automate the building of J2EE apps and components with Ant and XDoclet Techniques for automating Java testing using JUnit Procedures for automating servlet, JSP, and other J2EE testing using Cactus Ways to automate Swing testing with Jemmy, JFCUnit, and Abbot How to manage projects using Maven Techniques for automating continuous integration with AntHill and Cruise Control How to harness plugins for JUnit, Cactus, and Ant in the Eclipse IDE Ways to implement Extreme Programming best practices Who is this book for? This book is for enterprise Java developers who have a general familiarity with the XP methodology and want to put leading Java XP tools to work in the development process.
Author: Richard M. Reese
Publisher: Packt Publishing Ltd
ISBN: 1785281240
Category : Computers
Languages : en
Pages : 376
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Book Description
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.
Author: Kenneth Kousen
Publisher: Simon and Schuster
ISBN: 1638352267
Category : Computers
Languages : en
Pages : 546
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Book Description
Summary Making Java Groovy is a practical handbook for developers who want to blend Groovy into their day-to-day work with Java. It starts by introducing the key differences between Java and Groovy—and how you can use them to your advantage. Then, it guides you step-by-step through realistic development challenges, from web applications to web services to desktop applications, and shows how Groovy makes them easier to put into production. About this Book You don't need the full force of Java when you're writing a build script, a simple system utility, or a lightweight web app—but that's where Groovy shines brightest. This elegant JVM-based dynamic language extends and simplifies Java so you can concentrate on the task at hand instead of managing minute details and unnecessary complexity. Making Java Groov is a practical guide for developers who want to benefit from Groovy in their work with Java. It starts by introducing the key differences between Java and Groovy and how to use them to your advantage. Then, you'll focus on the situations you face every day, like consuming and creating RESTful web services, working with databases, and using the Spring framework. You'll also explore the great Groovy tools for build processes, testing, and deployment and learn how to write Groovy-based domain-specific languages that simplify Java development. Written for developers familiar with Java. No Groovy experience required. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. What's Inside Easier Java Closures, builders, and metaprogramming Gradle for builds, Spock for testing Groovy frameworks like Grails and Griffon About the Author Ken Kousen is an independent consultant and trainer specializing in Spring, Hibernate, Groovy, and Grails. Table of Contents PART 1: UP TO SPEED WITH GROOVY Why add Groovy to Java? Groovy by example Code-level integration Using Groovy features in Java PART 2: GROOVY TOOLS Build processes Testing Groovy and Java projects PART 3: GROOVY IN THE REAL WORLD The Spring framework Database access RESTful web services Building and testing web applications
