Offers 365 daily inspirational thoughts from The Road Less Traveled and The Different Drum that focus on the challenges of everyday life.

     Ignoring the boundaries of disciplines and schools and searching for novel fundamental ideas, theories, and practices, this international community integrates the full range of scientific inquiries that will help us to understand and survive on a complex planet. This volume collects essays from the past thirty years of research, in which contributors explain in clear and accessible language many of the deepest challenges and insights of complexity science. Explore the evolution of complex systems science with chapters from Nobel Laureates Murray Gell-Mann and Kenneth Arrow, as well as numerous pioneering complexity researchers, including John Holland, Brian Arthur, Robert May, Richard Lewontin, Jennifer Dunne, and Geoffrey West.

    He spent two years gathering information that demonstrates this and along the way interviewed more than a hundred experts in a number of different fields. Among them were parapsychologists, medical doctors, psychologists, psychiatrists, quantum physicists, and researchers into the true nature of reality. Specific examples are presented that indicate what happens when we die, for example that memories can be formed and retained despite a subject’s brain having been shutdown and the blood drained from it. Questions such as whether or not you will be able to communicate with living loved ones after death are addressed, if it is possible to be reborn, and what might be missing from reproductive theory to explain the various phenomena indicated in the many case histories and scientific investigations presented. All of us will someday cross the border to what Shakespeare called "The undiscovered country." As long as we must make that trip, wouldn’t it be smart to find out where we are going and what to expect when we get there?

    Haskell emerged in the last decade as a standard for lazy functional programming, a programming style where arguments are evaluated only when the value is actually needed. Haskell is a marvellous demonstration tool for logic and maths because its functional character allows implementations to remain very close to the concepts that get implemented, while the laziness permits smooth handling of infinite data structures.This book does not assume the reader to have previous experience with either programming or construction of formal proofs, but acquaintance with mathematical notation, at the level of secondary school mathematics is presumed. Everything one needs to know about mathematical reasoning or programming is explained as we go along. After proper digestion of the material in this book the reader will be able to write interesting programs, reason about their correctness, and document them in a clear fashion. The reader will also have learned how to set up mathematical proofs in a structured way, and how to read and digest mathematical proofs written by others.

    It was the worst school massacre in our nation's history. Can we prevent a tragedy like this from happening again?In Elliot Aronson's Nobody Left to Hate, on of our nation's leading social psychologists argues that the negative atmosphere in our schools--the exclusion, taunting, humiliation, and bullying--played a major role in triggering the pathological behavior of the shooters. At the very least, such an atmosphere makes schools an unpleasant experience for most normal students.But it doesn't have to be. Nobody Left to Hate offers concise, practical, and easy-to-apply strategies for creating a more supportive, stimulating, and compassionate environment in our schools. Based on decades of scientific research and classroom testing, these strategies explain how students can be taught to control their own impulses, how to respect others, and how to resolve conflicts amicably. In addition, they show teachers how to structure classes to promote cooperation, rather than competition, without sacrificing academics. On the contrary, education is greatly enhanced.For parents, teachers, or anyone concerned with what is happening in our schools, Nobody Left to Hate provides a simple and effective plan of action that will make their children's school not only a safe place, but a more humane place of learning.

    This is a presentation of the essential teaching of this direct path to freedom that focuses on the recognition and realization of the True Self. This book identifies the root cause of suffering as the identification with the mind and the belief that the psychological construct that is considered the "person" is actual. It is shown that this idea we have of who we are is an illusion that has been taken to be real and thus creates all forms of psychological suffering and confusion. The freedom from this illusion is shown to be available to anyone who is willing to recognize and realize the truth of who they are. This is a non-dual approach to psychological treatment that is becoming a new approach that has the potential to bring an end to all psychological disorders.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    The implications of their discoveries form tomorrow's headlines, yet Angier writes about the scientists themselves and not merely theri successes. 4-page photo insert.

    Each self-contained chapter consists of three sections. The first describes the statistic, including how it is used and what information it provides. The second section reviews how it works, how to calculate the formula, the strengths and weaknesses of the technique, and the conditions needed for its use. The final section provides examples that use and interpret the statistic. A glossary of terms and symbols is also included.New features in the second edition include:an interactive CD with PowerPoint presentations and problems for each chapter including an overview of the problem's solution; new chapters on basic research concepts including sampling, definitions of different types of variables, and basic research designs and one on nonparametric statistics; more graphs and more precise descriptions of each statistic; and a discussion of confidence intervals.This brief paperback is an ideal supplement for statistics, research methods, courses that use statistics, or as a reference tool to refresh one's memory about key concepts. The actual research examples are from psychology, education, and other social and behavioral sciences.Materials formerly available with this book on CD-ROM are now available for download from our website www.psypress.com. Go to the book's page and look for the 'Download' link in the right-hand column.

    Its enable us to sense, measure, and understand aspects of our existence in ways never before possible. The Human Face of Big Data captures, in glorious photographs and moving essays, an extraordinary revolution sweeping, almost invisibly, through business, academia, government, healthcare, and everyday life. It's already enabling us to provide a healthier life for our children. To provide our seniors with independence while keeping them safe. To help us conserve precious resources like water and energy. To alert us to tiny changes in our health, weeks or years before we develop a life-threatening illness. To peer into our own individual genetic makeup. To create new forms of life.  And soon, as many predict, to re-engineer our own species. And we've barely scratched the surface . . . Over the past decade, Rick Smolan and Jennifer Erwitt, co-founders of Against All Odds Productions, have produced a series of ambitious global projects in collaboration with hundreds of the world's leading photographers, writers, and graphic designers. Their Day in the Life projects were credited for creating a mass market for large-format illustrated books (rare was the coffee table book without one).  Today their projects aim at sparking global conversations about emerging topics ranging from the Internet (24 Hours in Cyberspace), to Microprocessors (One Digital Day), to how the human race is learning to heal itself, (The Power to Heal) to the global water crisis (Blue Planet Run). This year Smolan and Erwitt dispatched photographers and writers in every corner of the globe to explore the world of “Big Data” and to determine if it truly does, as many in the field claim, represent a brand new toolset for humanity, helping address the biggest challenges facing our species. The book features 10 essays by noted writers:Introduction: OCEANS OF DATA by Dan GardnerChapter 1: REFLECTIONS IN A DIGITAL MIRROR by Juan Enriquez, CEO, BiotechnomomyChapter 2: OUR DATA OURSELVES by Kate Green, the EconomistChapter 3: QUANTIFYING MYSELF by AJ Jacobs, EsquireChapter 4: DARK DATA by Marc Goodman, Future Crime InstituteChapter 5:  THE SENTIENT SENSOR MESH by Susan Karlin, Fast CompanyChapter 6: TAKING THE PULSE OF THE PLANET by Esther Dyson, EDventureChapter 7: CITIZEN SCIENCE by Gareth Cook, the Boston GlobeChapter 8: A DEMOGRAPH OF ONE by Michael Malone, Forbes magazineChapter 9: THE ART OF DATA by Aaron Koblin, Google Artist in ResidenceChapter 10: DATA DRIVEN by Jonathan Harris, Cowbird The book will also feature stunning info graphics from NIGEL HOLMES.1) GOOGLING GOOGLE: all the ways Google uses Data to help humanity2) DATA IS THE NEW OIL3) THE WORLD ACCORDING TO TWITTER4) AUCTIONING EYEBALLS: The world of Internet advertising5) FACEBOOK: A Billion Friends

    This book, which accompanies the major Channel 4 series, brings to life the hidden history of codes and code breaking. Since the birth of writing, there has also been the need for secrecy. The story of codes is the story of the brilliant men and women who used mathematics, linguistics, machines, computers, gut instinct, logic and detective work to encrypt and break these secrect messages and the effect their work has had on history. In each episode of "The Science of Secrecy" Simon Singh tells us a fascinating story from the history of codes: how the course of Crimean War was changed by the cracking of "unbreakable" Vigenere code; how the well-timed cracking of a single encoded telegram altered the course of World War I or how the mysteries of the Rosetta stone were revealed. The programme, and book, also investigates present day concerns about privacy on the internet and public key cryptography and looks to the future and the possibilities that quantum computing will radically change the science of secrecy in the 21st century.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    But fully 70 percent of digital transformations fail.Why? Tony Saldanha, a globally awarded industry thought-leader who led operations around the world and major digital changes at Procter & Gamble, discovered it's not due to innovation or technological problems. Rather, the devil is in the details: a lack of clear goals and a disciplined process for achieving them. In this book, Saldanha lays out a five-stage process for moving from digitally automating processes here and there to making digital technology the very backbone of your company. For each of these five stages, Saldanha describes two associated disciplines vital to the success of that stage and a checklist of questions to keep you on track.You want to disrupt before you are disrupted--be the next Netflix, not the next Blockbuster. Using dozens of case studies and his own considerable experience, Saldanha shows how digital transformation can be made routinely successful, and instead of representing an existential threat, it will become the opportunity of a lifetime.

    You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.To get you started--whether you're on Windows, OS X, or Linux--author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.Discover why the command line is an agile, scalable, and extensible technology. Even if you're already comfortable processing data with, say, Python or R, you'll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms