Thaler, and Cass R. Sunstein: a revelatory look at how we make decisionsNew York Times bestsellerNamed a Best Book of the Year by The Economist and the Financial Times Every day we make choices—about what to buy or eat, about financial investments or our children’s health and education, even about the causes we champion or the planet itself. Unfortunately, we often choose poorly. Nudge is about how we make these choices and how we can make better ones. Using dozens of eye-opening examples and drawing on decades of behavioral science research, Nobel Prize winner Richard H. Thaler and Harvard Law School professor Cass R. Sunstein show that no choice is ever presented to us in a neutral way, and that we are all susceptible to biases that can lead us to make bad decisions. But by knowing how people think, we can use sensible “choice architecture” to nudge people toward the best decisions for ourselves, our families, and our society, without restricting our freedom of choice.

    The book provides the tools needed to avoid usability surprises and improve product quality. Step-by-step information on which method to use at various stages during the development lifecycle are included, along with detailed information on how to run a usability test and the unique issues relating to international usability

    This design workshop begins with an examination of the fundamental elements of game design; then puts you to work in prototyping, playtesting and redesigning your own games with exercises that teach essential design skills. Workshop exercises require no background in programming or artwork, releasing you from the intricacies of electronic game production, so you can develop a working understanding of the essentials of game design.Features:* A design methodology used in the USC Interactive Media program, a cutting edge program funded in part of Electronic Arts. * Hands-on exercises demonstrate key concepts, and the design methodology* Insights from top industry game designers, including Noah Falstein, American McGee, Peter Molyneux

    Building on the successful top-down approach of previous editions, this fourth edition continues with an early emphasis on application-layer paradigms and application programming interfaces, encouraging a hands-on experience with protocols and networking concepts.

    Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter

    Their dedication and hard work have yielded an authoritative volume that defines and classifies mental disorders in order to improve diagnoses, treatment, and research.The criteria are concise and explicit, intended to facilitate an objective assessment of symptom presentations in a variety of clinical settings -- inpatient, outpatient, partial hospital, consultation-liaison, clinical, private practice, and primary care. New features and enhancements make DSM-5 easier to use across all settings:- The chapter organization reflects a lifespan approach, with disorders typically diagnosed in childhood (such as neurodevelopmental disorders) at the beginning of the manual, and those more typical of older adults (such as neurocognitive disorders) placed at the end. Also included are age-related factors specific to diagnosis. - The latest findings in neuroimaging and genetics have been integrated into each disorder along with gender and cultural considerations.- The revised organizational structure recognizes symptoms that span multiple diagnostic categories, providing new clinical insight in diagnosis. - Specific criteria have been streamlined, consolidated, or clarified to be consistent with clinical practice (including the consolidation of autism disorder, Asperger's syndrome, and pervasive developmental disorder into autism spectrum disorder; the streamlined classification of bipolar and depressive disorders; the restructuring of substance use disorders for consistency and clarity; and the enhanced specificity for major and mild neurocognitive disorders).- Dimensional assessments for research and validation of clinical results have been provided.- Both ICD-9-CM and ICD-10-CM codes are included for each disorder, and the organizational structure is consistent with the new ICD-11 in development.The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, is the most comprehensive, current, and critical resource for clinical practice available to today's mental health clinicians and researchers of all orientations. The information contained in the manual is also valuable to other physicians and health professionals, including psychologists, counselors, nurses, and occupational and rehabilitation therapists, as well as social workers and forensic and legal specialists.

    With step-by-step guidance, Validating Product Ideas shows you how to tackle the research to build the best possible product.

    They yearn to come up with a game—changing innovation like Apple's iPod, or create an entirely new category like Facebook. Many make genuine efforts to be innovative—they spend on R&D, bring in creative designers, hire innovation consultants. But they get disappointing results.Why? In The Design of Business, Roger Martin offers a compelling and provocative answer: we rely far too exclusively on analytical thinking, which merely refines current knowledge, producing small improvements to the status quo.To innovate and win, companies need design thinking. This form of thinking is rooted in how knowledge advances from one stage to another—from mystery (something we can't explain) to heuristic (a rule of thumb that guides us toward solution) to algorithm (a predictable formula for producing an answer) to code (when the formula becomes so predictable it can be fully automated). As knowledge advances across the stages, productivity grows and costs drop-creating massive value for companies.Martin shows how leading companies such as Procter & Gamble, Cirque du Soleil, RIM, and others use design thinking to push knowledge through the stages in ways that produce breakthrough innovations and competitive advantage.Filled with deep insights and fresh perspectives, The Design of Business reveals the true foundation of successful, profitable innovation.

    Meanwhile, people with important ideas--entrepreneurs, teachers, politicians, and journalists--struggle to make them "stick."In Made to Stick, Chip and Dan Heath reveal the anatomy of ideas that stick and explain ways to make ideas stickier, such as applying the human scale principle, using the Velcro Theory of Memory, and creating curiosity gaps. Along the way, we discover that sticky messages of all kinds--from the infamous "kidney theft ring" hoax to a coach's lessons on sportsmanship to a vision for a new product at Sony--draw their power from the same six traits.Made to Stick will transform the way you communicate. It's a fast-paced tour of success stories (and failures): the Nobel Prize-winning scientist who drank a glass of bacteria to prove a point about stomach ulcers; the charities who make use of the Mother Teresa Effect; the elementary-school teacher whose simulation actually prevented racial prejudice.Provocative, eye-opening, and often surprisingly funny, Made to Stick shows us the vital principles of winning ideas--and tells us how we can apply these rules to making our own messages stick.

    Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.

    Development activities are linked via handoffs between stages as practitioners move through the process. The lifecycle template concept introduced in this book can be tailored to any project environment, from large enterprise system development to commercial products. Whether a student or practitioner, you will come away with knowledge and understanding of how to create and refine interaction designs to ensure a quality user experience.

     At any given moment, somewhere in the world someone struggles with the same software design problems you have. You know you don't want to reinvent the wheel (or worse, a flat tire), so you look to Design Patterns--the lessons learned by those who've faced the same problems. With Design Patterns, you get to take advantage of the best practices and experience of others, so that you can spend your time on...something else. Something more challenging. Something more complex. Something more fun. You want to learn about the patterns that matter--why to use them, when to use them, how to use them (and when NOT to use them). But you don't just want to see how patterns look in a book, you want to know how they look "in the wild". In their native environment. In other words, in real world applications. You also want to learn how patterns are used in the Java API, and how to exploit Java's built-in pattern support in your own code. You want to learn the real OO design principles and why everything your boss told you about inheritance might be wrong (and what to do instead). You want to learn how those principles will help the next time you're up a creek without a design pattern. Most importantly, you want to learn the "secret language" of Design Patterns so that you can hold your own with your co-worker (and impress cocktail party guests) when he casually mentions his stunningly clever use of Command, Facade, Proxy, and Factory in between sips of a martini. You'll easily counter with your deep understanding of why Singleton isn't as simple as it sounds, how the Factory is so often misunderstood, or on the real relationship between Decorator, Facade and Adapter. With Head First Design Patterns, you'll avoid the embarrassment of thinking Decorator is something from the "Trading Spaces" show. Best of all, in a way that won't put you to sleep! We think your time is too important (and too short) to spend it struggling with academic texts. If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. Using the latest research in neurobiology, cognitive science, and learning theory, Head First Design Patterns will load patterns into your brain in a way that sticks. In a way that lets you put them to work immediately. In a way that makes you better at solving software design problems, and better at speaking the language of patterns with others on your team.

    Consultant Brown describes the ten basic deliverables as belonging to three basic types, thereby making it much easier to sort out who gets what and when. He wo

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    "His book is very compatible with XP. It is not about drawing pictures of a domain; it is about how you think of it, the language you use to talk about it, and how you organize your software to reflect your improving understanding of it. Eric thinks that learning about your problem domain is as likely to happen at the end of your project as at the beginning, and so refactoring is a big part of his technique. "The book is a fun read. Eric has lots of interesting stories, and he has a way with words. I see this book as essential reading for software developers--it is a future classic." --Ralph Johnson, author of Design Patterns "If you don't think you are getting value from your investment in object-oriented programming, this book will tell you what you've forgotten to do. "Eric Evans convincingly argues for the importance of domain modeling as the central focus of development and provides a solid framework and set of techniques for accomplishing it. This is timeless wisdom, and will hold up long after the methodologies du jour have gone out of fashion." --Dave Collins, author of Designing Object-Oriented User Interfaces "Eric weaves real-world experience modeling--and building--business applications into a practical, useful book. Written from the perspective of a trusted practitioner, Eric's descriptions of ubiquitous language, the benefits of sharing models with users, object life-cycle management, logical and physical application structuring, and the process and results of deep refactoring are major contributions to our field." --Luke Hohmann, author of Beyond Software Architecture "This book belongs on the shelf of every thoughtful software developer." --Kent Beck "What Eric has managed to capture is a part of the design process that experienced object designers have always used, but that we have been singularly unsuccessful as a group in conveying to the rest of the industry. We've given away bits and pieces of this knowledge...but we've never organized and systematized the principles of building domain logic. This book is important." --Kyle Brown, author of Enterprise Java(TM) Programming with IBM(R) WebSphere(R) The software development community widely acknowledges that domain modeling is central to software design. Through domain models, software developers are able to express rich functionality and translate it into a software implementation that truly serves the needs of its users. But despite its obvious importance, there are few practical resources that explain how to incorporate effective domain modeling into the software development process. Domain-Driven Design fills that need. This is not a book about specific technologies. It offers readers a systematic approach to domain-driven design, presenting an extensive set of design best practices, experience-based techniques, and fundamental principles that facilitate the development of software projects facing complex domains. Intertwining design and development practice, this book incorporates numerous examples based on actual projects to illustrate the application of domain-driven design to real-world software development. Readers learn how to use a domain model to make a complex development effort more focused and dynamic. A core of best practices and standard patterns provides a common language for the development team. A shift in emphasis--refactoring not just the code but the model underlying the code--in combination with the frequent iterations of Agile development leads to deeper insight into domains and enhanced communication between domain expert and programmer. Domain-Driven Design then builds on this foundation, and addresses modeling and design for complex systems and larger organizations.Specific topics covered include:Getting all team members to speak the same language Connecting model and implementation more deeply Sharpening key distinctions in a model Managing the lifecycle of a domain object Writing domain code that is safe to combine in elaborate ways Making complex code obvious and predictable Formulating a domain vision statement Distilling the core of a complex domain Digging out implicit concepts needed in the model Applying analysis patterns Relating design patterns to the model Maintaining model integrity in a large system Dealing with coexisting models on the same project Organizing systems with large-scale structures Recognizing and responding to modeling breakthroughs With this book in hand, object-oriented developers, system analysts, and designers will have the guidance they need to organize and focus their work, create rich and useful domain models, and leverage those models into quality, long-lasting software implementations.