By following the recommendations of the Association of Computing Machinery's Java Task Force, this first edition text adopts a modern objects-first approach that introduces readers to useful hierarchies from the very beginning.KEY TOPICS: Introduction; Programming by Example; Expressions; Statement Forms; Methods; Objects and Classes; Objects and Memory; Strings and Characters; Object-Oriented Graphics; Event-Driven Programs; Arrays and ArrayLists; Searching and Sorting; Collection Classes; Looking Ahead.MARKET: A modern objects-first approach to the Java programming language that introduces readers to useful class hierarchies from the very beginning.

    This groundbreaking new book sets out the principles and technical practices that enable rapid, incremental delivery of high quality, valuable new functionality to users. Through automation of the build, deployment, and testing process, and improved collaboration between developers, testers, and operations, delivery teams can get changes released in a matter of hours-- sometimes even minutes-no matter what the size of a project or the complexity of its code base. Jez Humble and David Farley begin by presenting the foundations of a rapid, reliable, low-risk delivery process. Next, they introduce the "deployment pipeline," an automated process for managing all changes, from check-in to release. Finally, they discuss the "ecosystem" needed to support continuous delivery, from infrastructure, data and configuration management to governance. The authors introduce state-of-the-art techniques, including automated infrastructure management and data migration, and the use of virtualization. For each, they review key issues, identify best practices, and demonstrate how to mitigate risks. Coverage includes - Automating all facets of building, integrating, testing, and deploying software - Implementing deployment pipelines at team and organizational levels - Improving collaboration between developers, testers, and operations - Developing features incrementally on large and distributed teams - Implementing an effective configuration management strategy - Automating acceptance testing, from analysis to implementation - Testing capacity and other non-functional requirements - Implementing continuous deployment and zero-downtime releases - Managing infrastructure, data, components and dependencies - Navigating risk management, compliance, and auditing Whether you're a developer, systems administrator, tester, or manager, this book will help your organization move from idea to release faster than ever--so you can deliver value to your business rapidly and reliably.

    For the most part the book is a discussion of good writing style and effective research strategies. Some of the material is accepted wisdom, some is controversial, and some is my opinions. Although the book is brief, it is designed to be comprehensive: some readers may be interested in exploring topics further, but for most readers this book should be suf?cient. The ?rst edition of this book was almost entirely about writing. This e- tion, partly in response to reader feedback and partly in response to issues that arose in my ownexperiences as an advisor, researcher, and referee, is also about research methods. Indeed, the two topics writing about and doing research are not clearly separated. It is a small step from asking how do I write? to askingwhatisitthatIwriteabout? As previously, the guidance on writing focuses on research, but much of the material is applicable to general technical and professional communication. Likewise, the guidance on the practice of research has broader lessons. A pr- titioner trying a new algorithm or explaining to colleagues why one solution is preferable to another should be con?dent that the arguments are built on robust foundations. And, while this edition has a stronger emphasis on research than did the ?rst, nothing has been deleted; there is additional material on research, but the guidance on writing has not been taken away."

    Identity Theft. Corporate Espionage. National secrets compromised. Can anyone promise security in our digital world?The man who introduced cryptography to the boardroom says no. But in this fascinating read, he shows us how to come closer by developing security measures in terms of context, tools, and strategy. Security is a process, not a product – one that system administrators and corporate executives alike must understand to survive.This edition updated with new information about post-9/11 security.

    They are vehicles, a series of hypothetical, self-operating machines that exhibit increasingly intricate if not always successful or civilized behavior. Each of the vehicles in the series incorporates the essential features of all the earlier models and along the way they come to embody aggression, love, logic, manifestations of foresight, concept formation, creative thinking, personality, and free will. In a section of extensive biological notes, Braitenberg locates many elements of his fantasy in current brain research.

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    The Computer Revolution may be even more life-changing than the Industrial Revolution. We can do things with computers that could never be done before, and computers can do things for us that could never be done before.But our love of computers should not cloud our thinking about their limitations.We are told that computers are smarter than humans and that data mining can identify previously unknown truths, or make discoveries that will revolutionize our lives. Our lives may well be changed, but not necessarily for the better. Computers are very good at discovering patterns, but are uselessin judging whether the unearthed patterns are sensible because computers do not think the way humans think.We fear that super-intelligent machines will decide to protect themselves by enslaving or eliminating humans. But the real danger is not that computers are smarter than us, but that we think computers are smarter than us and, so, trust computers to make important decisions for us.The AI Delusion explains why we should not be intimidated into thinking that computers are infallible, that data-mining is knowledge discovery, and that black boxes should be trusted.

    Many examples are taken from real-world projects. The book focuses on high-level design as well as the gritty details of the Python syntax. The provided exercises inspire the reader to think about his or her own code, rather than providing solved problems. If you're new to Object Oriented Programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply Object Oriented Programming in Python, this is the book for you. If you are an object-oriented programmer for other languages, you too will find this book a useful introduction to Python, as it uses terminology you are already familiar with. Python 2 programmers seeking a leg up in the new world of Python 3 will also find the book beneficial, and you need not necessarily know Python 2.

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    Admittedly, computers now play chess at the grandmaster level, but do they understand the game as we do? Can a computer eventually do everything a human mind can do? In this absorbing and frequently contentious book, Roger Penrose--eminent physicist and winner, with Stephen Hawking, of the prestigious Wolf prize--puts forward his view that there are some facets of human thinking that can never be emulated by a machine. Penrose examines what physics and mathematics can tell us about how the mind works, what they can't, and what we need to know to understand the physical processes of consciousness. He is among a growing number of physicists who think Einstein wasn't being stubborn when he said his little finger told him that quantum mechanics is incomplete, and he concludes that laws even deeper than quantum mechanics are essential for the operation of a mind. To support this contention, Penrose takes the reader on a dazzling tour that covers such topics as complex numbers, Turing machines, complexity theory, quantum mechanics, formal systems, Godel undecidability, phase spaces, Hilbert spaces, black holes, white holes, Hawking radiation, entropy, quasicrystals, the structure of the brain, and scores of other subjects. The Emperor's New Mind will appeal to anyone with a serious interest in modern physics and its relation to philosophical issues, as well as to physicists, mathematicians, philosophers and those on either side of the AI debate.

    If you're like most people, you probably believe that humans are the most intelligent animals on our planet. But there's another kind of entity that can be far smarter: groups of people. In this groundbreaking book, Thomas Malone, the founding director of the MIT Center for Collective Intelligence, shows how groups of people working together in superminds -- like hierarchies, markets, democracies, and communities -- have been responsible for almost all human achievements in business, government, science, and beyond. And these collectively intelligent human groups are about to get much smarter. Using dozens of striking examples and case studies, Malone shows how computers can help create more intelligent superminds simply by connecting humans to one another in a variety of rich, new ways. And although it will probably happen more gradually than many people expect, artificially intelligent computers will amplify the power of these superminds by doing increasingly complex kinds of thinking. Together, these changes will have far-reaching implications for everything from the way we buy groceries and plan business strategies to how we respond to climate change, and even for democracy itself. By understanding how these collectively intelligent groups work, we can learn how to harness their genius to achieve our human goals. Drawing on cutting-edge science and insights from a remarkable range of disciplines, Superminds articulates a bold -- and utterly fascinating -- picture of the future that will change the ways you work and live, both with other people and with computers.

    This book draws on material Michael created for his renowned Object Mentor seminars, techniques Michael has used in mentoring to help hundreds of developers, technical managers, and testers bring their legacy systems under control. The topics covered include: Understanding the mechanics of software change, adding features, fixing bugs, improving design, optimizing performance Getting legacy code into a test harness Writing tests that protect you against introducing new problems Techniques that can be used with any language or platform, with examples in Java, C++, C, and C# Accurately identifying where code changes need to be made Coping with legacy systems that aren't object-oriented Handling applications that don't seem to have any structureThis book also includes a catalog of twenty-four dependency-breaking techniques that help you work with program elements in isolation and make safer changes.

    Bleak tools of the cold war, they embodied the rigid organization and mechanical conformity that made the military-industrial complex possible. But by the 1990s—and the dawn of the Internet—computers started to represent a very different kind of world: a collaborative and digital utopia modeled on the communal ideals of the hippies who so vehemently rebelled against the cold war establishment in the first place. From Counterculture to Cyberculture is the first book to explore this extraordinary and ironic transformation. Fred Turner here traces the previously untold story of a highly influential group of San Francisco Bay–area entrepreneurs: Stewart Brand and the Whole Earth network. Between 1968 and 1998, via such familiar venues as the National Book Award–winning Whole Earth Catalog, the computer conferencing system known as WELL, and, ultimately, the launch of the wildly successful Wired magazine, Brand and his colleagues brokered a long-running collaboration between San Francisco flower power and the emerging technological hub of Silicon Valley. Thanks to their vision, counterculturalists and technologists alike joined together to reimagine computers as tools for personal liberation, the building of virtual and decidedly alternative communities, and the exploration of bold new social frontiers. Shedding new light on how our networked culture came to be, this fascinating book reminds us that the distance between the Grateful Dead and Google, between Ken Kesey and the computer itself, is not as great as we might think.

    This book is focused on the details of data analysis that sometimes fall through the cracks in traditional statistics classes and textbooks. It is based in part on the authors blog posts, lecture materials, and tutorials. The author is one of the co-developers of the Johns Hopkins Specialization in Data Science the largest data science program in the world that has enrolled more than 1.76 million people. The book is useful as a companion to introductory courses in data science or data analysis. It is also a useful reference tool for people tasked with reading and critiquing data analyses. It is based on the authors popular open-source guides available through his Github account (https://github.com/jtleek). The paper is also available through Leanpub (https://leanpub.com/datastyle), if the book is purchased on that platform you are entitled to lifetime free updates.

    The Mikado Method is a process for surfacing the dependencies in a codebase, so that you can systematically eliminate technical debt and get things done.It gets its name from a simple game commonly known as "pick-up sticks." You start with a jumbled pile of sticks. The goal is to remove the Mikado, or Emperor, stick without disturbing the others. Players carefully remove sticks one at a time, leaving the rest of the heap intact, slowly exposing the Mikado. The game is a great metaphor for eliminating technical debt—carefully extracting each intertwined dependency until you're able to successfully resolve the central issue and move on.The Mikado Method is a book by the creators of this process. It describes a pragmatic, straightforward, and empirical method to plan and perform non-trivial technical improvements on an existing software system. The method has simple rules, but the applicability is vast. As you read, you'll practice a step-by-step system for identifying the scope and nature of your technical debt, mapping the key dependencies, and determining the safest way to approach the "Mikado"-your goal. A natural byproduct of this process is the Mikado Graph, a minimalistic, relevant, just-in-time roadmap and information radiator that reflects deep understanding of how your system works.