Author: John Ferguson Smart Publisher: "O'Reilly Media, Inc." ISBN: 0596527934 Category : Computers Languages : en Pages : 910
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
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
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: Chris Tyler Publisher: "O'Reilly Media, Inc." ISBN: 0596101953 Category : Computers Languages : en Pages : 273
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: Joshua Engel Publisher: Addison-Wesley Professional ISBN: 9780201309720 Category : Computers Languages : en Pages : 518
Book Description
The Java Virtual Machine (JVM) is the underlying technology behind Java's most distinctive features including size, security and cross-platform delivery. This guide shows programmers how to write programs for the Java Virtual Machine.
Author: Matt Wynne Publisher: Pragmatic Bookshelf ISBN: 1680504967 Category : Computers Languages : en Pages : 450
Book Description
Your customers want rock-solid, bug-free software that does exactly what they expect it to do. Yet they can't always articulate their ideas clearly enough for you to turn them into code. You need Cucumber: a testing, communication, and requirements tool-all rolled into one. All the code in this book is updated for Cucumber 2.4, Rails 5, and RSpec 3.5. Express your customers' wild ideas as a set of clear, executable specifications that everyone on the team can read. Feed those examples into Cucumber and let it guide your development. Build just the right code to keep your customers happy. You can use Cucumber to test almost any system or any platform. Get started by using the core features of Cucumber and working with Cucumber's Gherkin DSL to describe-in plain language-the behavior your customers want from the system. Then write Ruby code that interprets those plain-language specifications and checks them against your application. Next, consolidate the knowledge you've gained with a worked example, where you'll learn more advanced Cucumber techniques, test asynchronous systems, and test systems that use a database. Recipes highlight some of the most difficult and commonly seen situations the authors have helped teams solve. With these patterns and techniques, test Ajax-heavy web applications with Capybara and Selenium, REST web services, Ruby on Rails applications, command-line applications, legacy applications, and more. Written by the creator of Cucumber and the co-founders of Cucumber Ltd., this authoritative guide will give you and your team all the knowledge you need to start using Cucumber with confidence. What You Need: Windows, Mac OS X (with XCode) or Linux, Ruby 1.9.2 and upwards, Cucumber 2.4, Rails 5, and RSpec 3.5
Author: Bryan Burns Publisher: "O'Reilly Media, Inc." ISBN: 0596554818 Category : Computers Languages : en Pages : 858
Book Description
What if you could sit down with some of the most talented security engineers in the world and ask any network security question you wanted? Security Power Tools lets you do exactly that! Members of Juniper Networks' Security Engineering team and a few guest experts reveal how to use, tweak, and push the most popular network security applications, utilities, and tools available using Windows, Linux, Mac OS X, and Unix platforms. Designed to be browsed, Security Power Tools offers you multiple approaches to network security via 23 cross-referenced chapters that review the best security tools on the planet for both black hat techniques and white hat defense tactics. It's a must-have reference for network administrators, engineers and consultants with tips, tricks, and how-to advice for an assortment of freeware and commercial tools, ranging from intermediate level command-line operations to advanced programming of self-hiding exploits. Security Power Tools details best practices for: Reconnaissance -- including tools for network scanning such as nmap; vulnerability scanning tools for Windows and Linux; LAN reconnaissance; tools to help with wireless reconnaissance; and custom packet generation Penetration -- such as the Metasploit framework for automated penetration of remote computers; tools to find wireless networks; exploitation framework applications; and tricks and tools to manipulate shellcodes Control -- including the configuration of several tools for use as backdoors; and a review of known rootkits for Windows and Linux Defense -- including host-based firewalls; host hardening for Windows and Linux networks; communication security with ssh; email security and anti-malware; and device security testing Monitoring -- such as tools to capture, and analyze packets; network monitoring with Honeyd and snort; and host monitoring of production servers for file changes Discovery -- including The Forensic Toolkit, SysInternals and other popular forensic tools; application fuzzer and fuzzing techniques; and the art of binary reverse engineering using tools like Interactive Disassembler and Ollydbg A practical and timely network security ethics chapter written by a Stanford University professor of law completes the suite of topics and makes this book a goldmine of security information. Save yourself a ton of headaches and be prepared for any network security dilemma with Security Power Tools.
Author: Richard M. Reese Publisher: Packt Publishing Ltd ISBN: 1785281240 Category : Computers Languages : en Pages : 376
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: Andrei Sorin Publisher: Andsor Books ISBN: 0986938904 Category : Science Languages : en Pages : 934
Book Description
Addressing general readers as well as software practitioners, "Software and Mind" discusses the fallacies of the mechanistic ideology and the degradation of minds caused by these fallacies. Mechanism holds that every aspect of the world can be represented as a simple hierarchical structure of entities. But, while useful in fields like mathematics and manufacturing, this idea is generally worthless, because most aspects of the world are too complex to be reduced to simple hierarchical structures. Our software-related affairs, in particular, cannot be represented in this fashion. And yet, all programming theories and development systems, and all software applications, attempt to reduce real-world problems to neat hierarchical structures of data, operations, and features. Using Karl Popper's famous principles of demarcation between science and pseudoscience, the book shows that the mechanistic ideology has turned most of our software-related activities into pseudoscientific pursuits. Using mechanism as warrant, the software elites are promoting invalid, even fraudulent, software notions. They force us to depend on generic, inferior systems, instead of allowing us to develop software skills and to create our own systems. Software mechanism emulates the methods of manufacturing, and thereby restricts us to high levels of abstraction and simple, isolated structures. The benefits of software, however, can be attained only if we start with low-level elements and learn to create complex, interacting structures. Software, the book argues, is a non-mechanistic phenomenon. So it is akin to language, not to physical objects. Like language, it permits us to mirror the world in our minds and to communicate with it. Moreover, we increasingly depend on software in everything we do, in the same way that we depend on language. Thus, being restricted to mechanistic software is like thinking and communicating while being restricted to some ready-made sentences supplied by an elite. Ultimately, by impoverishing software, our elites are achieving what the totalitarian elite described by George Orwell in "Nineteen Eighty-Four" achieves by impoverishing language: they are degrading our minds.
Author: Yusuke Sugomori Publisher: Packt Publishing Ltd ISBN: 1785283146 Category : Computers Languages : en Pages : 254
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.
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Author: John Ferguson Smart
Author: John Ferguson Smart
Author: Ian H. Witten
Author: Chris Tyler
Author: Joshua Engel
Author: Matt Wynne
Author: Bryan Burns
Author: Richard M. Reese
Author: Andrei Sorin
Author: Yusuke Sugomori