Discover and master the fiery temperament shared by great leaders, entrepreneurs, artists and AD/HD-ers. Are you: - Impulsive? - Risk-taking? - Distractible? - Sensation-seeking? - Insightful or Intuitive? Do you: - Crave risk and excitement? - Have an addictive personality? - Rebel against authority? - Think differently? Then you are a DaVinci. Discover the secret genius that drives risk-takers, rebels, entrepreneurs, artists and ad/hd-ers to achieve greatness. Learn how to express this fire and harness it productively. About the Author Garret LoPorto, has been featured in The New York Times, Money Magazine, The Boston Globe and The London Financial Times. He is a successful entrepreneur, CEO, presenter at MIT, U.S. & International patent-pending inventor, and father of two children. He lives with his wife and children in Concord, Massachusetts.

    Through his own personal story and those of nine other Rangers, Barber illuminates fundamental lessons about what it really takes to win. These first-person accounts of trial and triumph highlight the importance and the inherent truth of the Army's most fundamental leadership principles: seeking and taking responsibility for your actions, and knowing yourself and seeking self-improvement. Adhering to those principles--and putting them at the core of your organization--will push you and your company to do more and do it better.

    Reflecting the need for even minor programming in today's model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.Web ResourceThe book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

    Think of the familiar map of the New York City subway system, or a diagram of the human brain. Successful visualizations are beautiful not only for their aesthetic design, but also for elegant layers of detail that efficiently generate insight and new understanding.This book examines the methods of two dozen visualization experts who approach their projects from a variety of perspectives -- as artists, designers, commentators, scientists, analysts, statisticians, and more. Together they demonstrate how visualization can help us make sense of the world.Explore the importance of storytelling with a simple visualization exerciseLearn how color conveys information that our brains recognize before we're fully aware of itDiscover how the books we buy and the people we associate with reveal clues to our deeper selvesRecognize a method to the madness of air travel with a visualization of civilian air trafficFind out how researchers investigate unknown phenomena, from initial sketches to published papers Contributors include:Nick Bilton, Michael E. Driscoll, Jonathan Feinberg, Danyel Fisher, Jessica Hagy, Gregor Hochmuth, Todd Holloway, Noah Iliinsky, Eddie Jabbour, Valdean Klump, Aaron Koblin, Robert Kosara, Valdis Krebs, JoAnn Kuchera-Morin et al., Andrew Odewahn, Adam Perer, Anders Persson, Maximilian Schich, Matthias Shapiro, Julie Steele, Moritz Stefaner, Jer Thorp, Fernanda Viegas, Martin Wattenberg, and Michael Young.

    It is a conversational book that feels easy and informative. This short and lucid book covers everything important, with concrete examples, and invites the reader to join this field. The chapters in the book are organized for a typical one-semester course. The book contains case-lets from real-world stories at the beginning of every chapter. There is a running case study across the chapters as exercises. This book is designed to provide a student with the intuition behind this evolving area, along with a solid toolset of the major data mining techniques and platforms. Students across a variety of academic disciplines, including business, computer science, statistics, engineering, and others are attracted to the idea of discovering new insights and ideas from data. This book can also be gainfully used by executives, managers, analysts, professors, doctors, accountants, and other professionals to learn how to make sense of the data coming their way. This is a lucid flowing book that one can finish in one sitting, or can return to it again and again for insights and techniques. Table of Contents Chapter 1: Wholeness of Business Intelligence and Data Mining Chapter 2: Business Intelligence Concepts & Applications Chapter 3: Data Warehousing Chapter 4: Data Mining Chapter 5: Decision Trees Chapter 6: Regression Models Chapter 7: Artificial Neural Networks Chapter 8: Cluster Analysis Chapter 9: Association Rule Mining Chapter 10: Text Mining Chapter 11: Web Mining Chapter 12: Big Data Chapter 13: Data Modeling Primer Appendix: Data Mining Tutorial using Weka

    Lean Analytics steers you in the right direction.This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without.Understand Lean Startup, analytics fundamentals, and the data-driven mindsetLook at six sample business models and how they map to new ventures of all sizesFind the One Metric That Matters to youLearn how to draw a line in the sand, so you’ll know it’s time to move forwardApply Lean Analytics principles to large enterprises and established products

    The book makes clear that applied microeconometrics is about the estimation of marginal and treatment effects, and that parametric estimation is simply a means to this end. It also clarifies the distinction between causality and statistical association. The book focuses specifically on cross section and panel data methods. Population assumptions are stated separately from sampling assumptions, leading to simple statements as well as to important insights. The unified approach to linear and nonlinear models and to cross section and panel data enables straightforward coverage of more advanced methods. The numerous end-of-chapter problems are an important component of the book. Some problems contain important points not fully described in the text, and others cover new ideas that can be analyzed using tools presented in the current and previous chapters. Several problems require the use of the data sets located at the author's website.

    Most people won't experience the same retirement that their parents did, nor do they necessarily want to. Page by page, top financial planner Mitch Anthony reveals how new opportunities will enable individuals to create tailor-made retirements. He includes new research and studies to back his insights and introduces readers to important concepts such as "wealthcare" and "return on life." Filled with engaging anecdotes and inspirational suggestions, this book will motivate readers to rethink the way they retire.

    Jason Briggs, author of the popular online tutorial "Snake Wrangling for Kids," begins with the basics of how to install Python and write simple commands. In bite-sized chapters, he instructs readers on the essentials of Python, including how to use Python's extensive standard library, the difference between strings and lists, and using for-loops and while-loops. By the end of the book, readers have built a game and created drawings with Python's graphics library, Turtle. Each chapter closes with fun and relevant exercises that challenge the reader to put their newly acquired knowledge to the test.

    Fortunately, Jon McGee is an ideal guide through this dynamic marketplace. In Breakpoint, he argues that higher education is in the midst of an extraordinary moment of demographic, economic, and cultural transition that has significant implications for how colleges understand their mission, their market, and their management. Drawing from an extensive assessment of demographic and economic trends, McGee presents a broad and integrative picture of these changes while stressing the importance of decisive campus leadership. He describes the key forces that influence higher education and provides a framework from which trustees, presidents, administrators, faculty, and policy makers can address pressing issues in the aftermath of the Great Recession.Although McGee avoids endorsing one-size-fits-all solutions, he suggests a number of concrete strategies for handling prospective students and developing pedagogical practices, curricular content and delivery, and management structures. Practical and compelling, Breakpoint will help higher education leaders make choices that advance their institutional values and serve their students and the common good for generations to come.

    The best-selling banjo method in the world! Earl Scruggs's legendary method has helped thousands of banjo players get their start. The Revised and Enhanced Edition features more songs, updated lessons, and many other improvements. It includes everything you need to know to start playing banjo, including: a history of the 5-string banjo, getting acquainted with the banjo, Scruggs tuners, how to read music, chords, how to read tablature, right-hand rolls and left-hand techniques, banjo tunings, exercises in picking, over 40 songs, how to build a banjo, autobiographical notes, and much more! The book/audio version includes recordings of Earl Scruggs playing and explaining over 60 examples! Audio is accessed online using the unique code inside the book and can be streamed or downloaded. The audio files include PLAYBACK+, a multi-functional audio player that allows you to slow down audio without changing pitch, set loop points, change keys, and pan left or right.

    Many Canadians who own their home have never considered buying a second property. And nearly one-third of retirees are worried about running out of money. The Real Estate Retirement Plan shows how homeowners can use the tools already available to them — their mortgages — to access the initial capital to invest and prepare for their retirement. This is a proven, validated antidote to today’s historically low savings rates, poor current rates of return, and pressure on CPP and health care.With examples and a detailed discussion of the principles and mechanics, Calum Ross and Simon Giannini demystify real-estate investing and make an irrefutable case for borrowing to invest.

    In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn’t confined to abstract incidents that never occur in real life, but rather touches everything we do—the whole world is shot through with it.Math allows us to see the hidden structures underneath the messy and chaotic surface of our world. It’s a science of not being wrong, hammered out by centuries of hard work and argument. Armed with the tools of mathematics, we can see through to the true meaning of information we take for granted: How early should you get to the airport? What does “public opinion” really represent? Why do tall parents have shorter children? Who really won Florida in 2000? And how likely are you, really, to develop cancer?How Not to Be Wrong presents the surprising revelations behind all of these questions and many more, using the mathematician’s method of analyzing life and exposing the hard-won insights of the academic community to the layman—minus the jargon. Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia’s views on crime and punishment, the psychology of slime molds, what Facebook can and can’t figure out about you, and the existence of God.Ellenberg pulls from history as well as from the latest theoretical developments to provide those not trained in math with the knowledge they need. Math, as Ellenberg says, is “an atomic-powered prosthesis that you attach to your common sense, vastly multiplying its reach and strength.” With the tools of mathematics in hand, you can understand the world in a deeper, more meaningful way. How Not to Be Wrong will show you how.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    KEY TOPICS: Specific, practical strategies include ways to get students active from the start through activities that build teamwork and immediately get them thinking about the subject matter. 101 activities include ice-breakers for the beginning of class, strategies for the middle of a lesson, and concluding exercises to foster student reflection and future application. In addition, these activities are designed to enliven learning, deepen understanding, and promote retention. Designed for the preservice and inservice teacher, this book is effective for anyone teaching in middle schools, high schools, colleges, and centers for adult education. For professionals working in middle school/secondary school education.