With this hands-on guide, you'll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python's core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work"

    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

    We’re told that learning is all self-discipline, that we must confine ourselves to designated study areas, turn off the music, and maintain a strict ritual if we want to ace that test, memorize that presentation, or nail that piano recital.   But what if almost everything we were told about learning is wrong? And what if there was a way to achieve more with less effort?   In How We Learn, award-winning science reporter Benedict Carey sifts through decades of education research and landmark studies to uncover the truth about how our brains absorb and retain information. What he discovers is that, from the moment we are born, we are all learning quickly, efficiently, and automatically; but in our zeal to systematize the process we have ignored valuable, naturally enjoyable learning tools like forgetting, sleeping, and daydreaming. Is a dedicated desk in a quiet room really the best way to study? Can altering your routine improve your recall? Are there times when distraction is good? Is repetition necessary? Carey’s search for answers to these questions yields a wealth of strategies that make learning more a part of our everyday lives—and less of a chore.   By road testing many of the counterintuitive techniques described in this book, Carey shows how we can flex the neural muscles that make deep learning possible. Along the way he reveals why teachers should give final exams on the first day of class, why it’s wise to interleave subjects and concepts when learning any new skill, and when it’s smarter to stay up late prepping for that presentation than to rise early for one last cram session. And if this requires some suspension of disbelief, that’s because the research defies what we’ve been told, throughout our lives, about how best to learn.   The brain is not like a muscle, at least not in any straightforward sense. It is something else altogether, sensitive to mood, to timing, to circadian rhythms, as well as to location and environment. It doesn’t take orders well, to put it mildly. If the brain is a learning machine, then it is an eccentric one. In How We Learn, Benedict Carey shows us how to exploit its quirks to our advantage.  Praise for How We Learn“This book is a revelation. I feel as if I’ve owned a brain for fifty-four years and only now discovered the operating manual.”—Mary Roach, bestselling author of Stiff and Gulp“A welcome rejoinder to the faddish notion that learning is all about the hours put in.” —The New York Times Book Review   “A valuable, entertaining tool for educators, students and parents.” —Shelf Awareness   “How We Learn is more than a new approach to learning; it is a guide to making the most out of life. Who wouldn’t be interested in that?” —Scientific American   “I know of no other source that pulls together so much of what we know about the science of memory and couples it with practical, practicable advice.”—Daniel T. Willingham, professor of psychology at the University of Virginia

    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.

    From Edward Lorenz’s discovery of the Butterfly Effect, to Mitchell Feigenbaum’s calculation of a universal constant, to Benoit Mandelbrot’s concept of fractals, which created a new geometry of nature, Gleick’s engaging narrative focuses on the key figures whose genius converged to chart an innovative direction for science. In Chaos, Gleick makes the story of chaos theory not only fascinating but also accessible to beginners, and opens our eyes to a surprising new view of the universe.

    It could forever change how you experience and interact with your physical surroundings, open your eyes to the perversity of bad design and the desirability of good design, and raise your expectations about how things should be designed.B & W photographs and illustrations throughout.

    One million people can create new market for a business, spark a social movement, or effect political change. In 1996, a microtrend identified by Penn ("soccer moms") was crucial in re-electing President Clinton. With years of experience as one of world's most highly regarded pollsters, Mark Penn identifies the new microtrends sweeping the world: *Single women by choice: More often than ever before, they aren't waiting for Mr. Right. They are raising children by themselves and buying their own homes.*Splitters: A growing number of middle-class residents are shuttling between two homes, creating new communities and dynamics in the real estate market.*Sun Haters: Environmentalists, skin cancer survivors, and parents concerned about the impact the sun is having on our health.*Philo-semites: A growing number of people want to date Jewish men and women.*Classical Music Dads: Older men who are fathers in their 40's and 50's and taking on a larger role in the nurturing of their children and becoming an important factor in consumer culture for kids. Penn highlights everything from religion to politics, from leisure pursuits to relationships. MICROTRENDS will take the reader deep into the worlds of polling, targeting, and psychographic analysis, reaching tantalizing conclusions through engaging analysis.

    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.

    But in our zeal to instill the evaluation process with scientific rigor, we've gone from measuring performance to fixating on measuring itself. The result is a tyranny of metrics that threatens the quality of our lives and most important institutions. In this timely and powerful book, Jerry Muller uncovers the damage our obsession with metrics is causing--and shows how we can begin to fix the problem.Filled with examples from education, medicine, business and finance, government, the police and military, and philanthropy and foreign aid, this brief and accessible book explains why the seemingly irresistible pressure to quantify performance distorts and distracts, whether by encouraging "gaming the stats" or "teaching to the test." That's because what can and does get measured is not always worth measuring, may not be what we really want to know, and may draw effort away from the things we care about. Along the way, we learn why paying for measured performance doesn't work, why surgical scorecards may increase deaths, and much more. But metrics can be good when used as a complement to--rather than a replacement for--judgment based on personal experience, and Muller also gives examples of when metrics have been beneficial.Complete with a checklist of when and how to use metrics, The Tyranny of Metrics is an essential corrective to a rarely questioned trend that increasingly affects us all.

    

    What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us.In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

    Restructured into six parts, this new edition covers a wide spectrum of software processes from initial requirements solicitation through design and development.

    This new edition includes the latest research and case studies, and offers inspiring new and relevant stories of real people achieving extraordinary results.

    Rossi, Mark W. Lipsey, and Howard E. Freeman first published Evaluation: A Systematic Approach, more than 90,000 readers have considered it the premier text on how to design, implement, and appraise social programs through evaluation. In this, the completely revised Seventh Edition, authors Rossi and Lipsey include the latest techniques and approaches to evaluation as well as guidelines to tailor evaluations to fit programs and social contexts.With decades of hands-on experience conducting evaluations, the authors provide scores of examples to help students understand how evaluators deal with various critical issues. They include a glossary of key terms and concepts, making this the most comprehensive and authoritative evaluation text available.Thoroughly revised, the Seventh Edition now includes* Substantially more attention to outcome measurement* Lengthy discussions of program theory, including a section about detecting program effects and interpreting their practical significance* An augmented and updated discussion of major evaluation designs* A detailed exposition of meta-analysis as an approach to the synthesis of evaluation studies* Alternative approaches to evaluation* Examples of successful evaluations* Discussions of the political and social contexts of evaluation

    You’ll learn…• How a noise reduction headset at 35,000 feet led to the creation of Pepsi’s new trademarked signature sound.• How a worn down sneaker discovered in the home of an 11-year-old German boy led to LEGO’s incredible turnaround.• How a magnet found on a fridge in Siberia resulted in a U.S. supermarket revolution.• How a toy stuffed bear in a girl’s bedroom helped revolutionize a fashion retailer’s 1,000 stores in 20 different countries.• How an ordinary bracelet helped Jenny Craig increase customer loyalty by 159% in less than a year.• How the ergonomic layout of a car dashboard led to the redesign of the Roomba vacuum.