Not to worry: This book is the one place you can turn to find quick, non-intimidating, excellent design help. In The Non-Designer's Design Book, 2nd Edition, best-selling author Robin Williams turns her attention to the basic principles of good design and typography. All you have to do is follow her clearly explained concepts, and you'll begin producing more sophisticated, professional, and interesting pages immediately. Humor-infused, jargon-free prose interspersed with design exercises, quizzes, illustrations, and dozens of examples make learning a snap—which is just what audiences have come to expect from this best-selling author.

    A Whole New Mind takes readers to a daring new place, and a provocative and necessary new way of thinking about a future that's already here.

    Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call centre next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience.

    Long recognized as very applied and practical, Eggen and Kauchak's Educational Psychology: Windows on Classrooms, seventh edition is now even more applied and concise, giving students exactly what they need to know in the course. The author's hallmark cases remain, in both written and videotape format, to introduce real-world applications in a way that no other text can. Along with expanded applications to diversity (urban, suburban, and rural areas), technology, and a new pedagogical system that completely restructures how information is delivered in the book and will help students really understand what they should be getting out of every single chapter. The text now comes with two new DVDs of video material and an access code for the new Teacher Prep Website that will be automatically shrinkwrapped with all new copies of the text. Educational Psychology: Windows on Classrooms once again truly fulfills the promise of its title, giving students a window on the classrooms in which they will someday teach.

    Questioning—deeply, imaginatively, "beautifully"—can help us identify and solve problems, come up with game-changing ideas, and pursue fresh opportunities. So why are we often reluctant to ask "Why?"Berger's surprising findings reveal that even though children start out asking hundreds of questions a day, questioning "falls off a cliff" as kids enter school. In an education and business culture devised to reward rote answers over challenging inquiry, questioning isn't encouraged—and, in fact, is sometimes barely tolerated.And yet, as Berger shows, the most creative, successful people tend to be expert questioners. They've mastered the art of inquiry, raising questions no one else is asking—and finding powerful answers. The author takes us inside red-hot businesses like Google, Netflix, IDEO, and Airbnb to show how questioning is baked into their organizational DNA. He also shares inspiring stories of artists, teachers, entrepreneurs, basement tinkerers, and social activists who changed their lives and the world around them—by starting with a "beautiful question."Berger explores important questions, such as:- Why aren't we nurturing kids' natural ability to question—and what can parents and schools do about that?- Since questioning is a starting point for innovation, how might companies and business leaders begin to encourage and exploit it?- And most important, how can each of us re-ignite that questioning spark—and use inquiry as a powerful means to rethink and reinvent our lives?A More Beautiful Question outlines a practical Why / What If / How system of inquiry that can guide you through the process of innovative questioning—helping you find imaginative, powerful answers to your own "beautiful questions."

    This collection of previously published essays reminds us that many schools have veered off course in their day-to-day business. And it's a primer that, if taken seriously, can put schools back on the right track. --Educational LeadershipThrough his writings and speeches, Alfie Kohn has been stirring up controversy for years, demonstrating how the conventional wisdom about education often isn't supported by the available research, and illuminating gaps between our long-term goals for students and what actually goes on in schools. Now What to Look for in a Classroom brings together his most popular articles from Educational Leadership, Phi Delta Kappan, and Education Week--and also from The Atlantic Monthly, the Boston Globe, and other publications. From self-esteem to school uniforms, from grade inflation to character education, Kohn raises a series of provocative questions about the status quo in this collection of incisive essays. He challenges us to reconsider some of our most basic assumptions about children and education. Can good values really be instilled in students? What, if anything, lies behind the label of attention deficit disorder? Are there solid data to support our skepticism about watching TV? Might such allegedly enlightened practices as authentic assessment, logical consequences, and Total Quality education turn out to be detrimental? Whether he is explaining why cooperative learning can be so threatening or why detracking is so fiercely opposed, Kohn offers a fresh, informed, and frequently disconcerting perspective on the major issues in education. In the And, his critical examination of current practice is complemented by a vision of what schooling ought to be. Kohn argues for giving children more opportunity to participate in their own schooling, for transforming classrooms into caring communities, and for providing the kind of education that taps and nourishes children's curiosity. Through all these essays, Kohn calls us back to our own ideals, showing us how we can be more effective at helping students to become good learners and good people.

    Born in the mid-1990s to the mid-2000s and later, iGen is the first generation to spend their entire adolescence in the age of the smartphone. With social media and texting replacing other activities, iGen spends less time with their friends in person—perhaps why they are experiencing unprecedented levels of anxiety, depression, and loneliness. But technology is not the only thing that makes iGen distinct from every generation before them; they are also different in how they spend their time, how they behave, and in their attitudes toward religion, sexuality, and politics. They socialize in completely new ways, reject once sacred social taboos, and want different things from their lives and careers. More than previous generations, they are obsessed with safety, focused on tolerance, and have no patience for inequality. iGen is also growing up more slowly than previous generations: eighteen-year-olds look and act like fifteen-year-olds used to. As this new group of young people grows into adulthood, we all need to understand them: Friends and family need to look out for them; businesses must figure out how to recruit them and sell to them; colleges and universities must know how to educate and guide them. And members of iGen also need to understand themselves as they communicate with their elders and explain their views to their older peers. Because where iGen goes, so goes our nation—and the world.

    They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.

    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"

    In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect.Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor.In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile.The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values.This deeply researched and passionate book could not be more timely.Naomi Klein: "This book is downright scary."Ethan Zuckerman, MIT: "Should be required reading."Dorothy Roberts, author of Killing the Black Body: "A must-read for everyone concerned about modern tools of inequality in America."Astra Taylor, author of The People's Platform: "This is the single most important book about technology you will read this year."

    If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills

    This internationally recognized standard provides the essential tools to practice project management and deliver organizational results.