Fresh coats of paint and newly pasted posters appear overnight in cities across the world. New artists, new ideas, and new tactics displace faded images in a perpetual process of renewal and metamorphosis. From Los Angeles to Barcelona, Stockholm to Tokyo, Melbourne to Milan, wall spaces are a breeding ground for graphic and typographic forms as artists unleash their daily creations.Current graffiti art is reflective of the world around it. Using new materials and techniques, its innovators are creating a language of forms and images infused with contemporary graphic design and illustration. Fluent in branding and graphic imagery, they have been replacing tags with more personal logos and shifting from typographic to iconographic forms of communication.Street Logos is a worldwide celebration of these new developments in twenty-first-century graffiti, an essential sourcebook for all art and design professionals, and a delight to everyone excited by the vitality of the street.

    Underlying this trend is a single idea: the belief that our existence is understandable through computation, and more data is enough to help us build a better world.   In actual fact, we are lost in a sea of information, increasingly divided by fundamentalism, simplistic narratives, conspiracy theories, and post-factual politics. Meanwhile, those in power use our lack of understanding to further their own interests. Despite the accessibility of information, we’re living in a new Dark Age.   From rogue financial systems to shopping algorithms, from artificial intelligence to state secrecy, we no longer understand how our world is governed or presented to us. The media is filled with unverifiable speculation, much of it generated by anonymous software, while companies dominate their employees through surveillance and the threat of automation.   In his brilliant new work, leading artist and writer James Bridle excavates the limits of technology and how it aids our understanding of the world. Surveying the history of art, technology, and information systems, he explores the dark clouds that gather over our dreams of the digital sublime.

    Born in 1926 in France, over the course of his life he dabbled in drugs, politics, and the Paris SM scene, all whilst striving to understand the deep concepts of identity, knowledge, and power.From aesthetics to the penal system; from madness and civilisation to avant-garde literature, Foucault was happy to reject old models of thinking and replace them with versions that are still widely debated today. A major influence on Queer Theory and gender studies (he was openly gay and died of an AIDS-related illness in 1984), he also wrote on architecture, history, law, medicine, literature, politics and of course philosophy, and even managed a best-seller in France on a book dedicated to the history of systems of thought.Because of the complexity of his arguments, people trying to come to terms with his work have desperately sought introductory material that makes his theories clear and accessible for the beginner. Ideally suited for the Very Short Introductions series, Gary Gutting presents a comprehensive but non-systematic treatment of some highlights of Foucault's life and thought. Beginning with a brief biography to set the social and political stage, he then tackles Foucault's thoughts on literature, in particular the avant-garde scene; his philosophical and historical work; his treatment of knowledge and power in modern society; and his thoughts on sexuality.

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

    Everyone can ask questions, right? Unfortunately, that's not the case. Interviewing Users provides invaluable interviewing techniques and tools that enable you to conduct informative interviews with anyone. You'll move from simply gathering data to uncovering powerful insights about people.Interviewing Users will explain how to succeed with interviewing, including:* Embracing how other people see the world* Building rapport to create engaging and exciting interactions* Listening in order to build rapport.With this book, Steve Portigal uses stories and examples from his 15 years of experience to show how interviewing can be incorporated into the design process, helping you learn the best and right information to inform and inspire your design.

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    It has sold 30,000 copies in each edition and will continue to reach a huge academic audience.In this renowned book, Everett M. Rogers, professor and chair of the Department of Communication & Journalism at the University of New Mexico, explains how new ideas spread via communication channels over time. Such innovations are initially perceived as uncertain and even risky. To overcome this uncertainty, most people seek out others like themselves who have already adopted the new idea. Thus the diffusion process consists of a few individuals who first adopt an innovation, then spread the word among their circle of acquaintances--a process which typically takes months or years. But there are exceptions: use of the Internet in the 1990s, for example, may have spread more rapidly than any other innovation in the history of humankind. Furthermore, the Internet is changing the very nature of diffusion by decreasing the importance of physical distance between people. The fifth edition addresses the spread of the Internet, and how it has transformed the way human beings communicate and adopt new ideas.

    Service Design is a bit of a buzzword these days and has gained a lot of interest from various fields. This book, assembled to describe and illustrate the emerging field of service design, was brought together using exactly the same co-creative and user-centred approaches you can read and learn about inside. The boundaries between products and services are blurring and it is time for a different way of thinking: this is service design thinking.A set of 23 international authors and even more online contributors from the global service design community invested their knwoledge, experience and passion together to create this book. It introduces service design thinking in a manner accessible to beginners and students, it broadens the knowledge and can act as a resource for experienced design professionals.

    It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.

    It is also the most powerful, and in some ways, the most confusing. What do accessible, content-focused standards-based web designers and front-end developers need to know? And how can we harness the power of HTML5 in today’s browsers?In this brilliant and entertaining user’s guide, Jeremy Keith cuts to the chase, with crisp, clear, practical examples, and his patented twinkle and charm.

    Redesigning your home page won't help. Investing in a new content management system won't fix it, either. So, where do you start? Without meaningful content, your website isn't worth much to your key audiences. But creating (and caring for) "meaningful" content is far more complicated than we're often willing to acknowledge. Content Strategy for the Web explains how to create and deliver useful, usable content for your online audiences, when and where they need it most. It also shares content best practices so you can get your next website redesign right, on time and on budget. For the first time, you'll: See content strategy (and its business value) explained in plain languageFind out why so many web projects implode in the content development phase ... and how to avoid the associated, unnecessary costs and delaysLearn how to audit and analyze your contentMake smarter, achievable decisions about which content to create and howFind out how to maintain consistent, accurate, compelling content over timeGet solid, practical advice on staffing for content-related roles and responsibilities "

    If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others. Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in Head First Data Analysis is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool. You'll learn how to:Determine which data sources to use for collecting information Assess data quality and distinguish signal from noise Build basic data models to illuminate patterns, and assimilate new information into the models Cope with ambiguous information Design experiments to test hypotheses and draw conclusions Use segmentation to organize your data within discrete market groups Visualize data distributions to reveal new relationships and persuade others Predict the future with sampling and probability models Clean your data to make it useful Communicate the results of your analysis to your audience Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Data Analysis uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

    It provides dozens of new examples from actual research studies are used to provide illustrations of concepts and methods. Key terms are now called out and defined in boxes at the bottom of the pages where they appear, for easier study and review. In chapter 1, there are now separate descriptions and examples of the steps in the research process for quantitative and qualitative approaches, to underscore some of the fundamental differences. Chapter 2 has new discussions of participatory action research, instrumental and reflexive knowledge, the various audiences for social research findings, and researcher autonomy when research is commissioned. The discussion of social theories in Chapter 3 now covers levels of abstraction, and relationships among concepts

    Clear instructions, fun exercises and example-filled pages help readers to master the fundamental techniques of graphic art and design.