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.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    But as Robert Bryce makes clear in this provocative book, that vision needs a major re-vision. We cannot—and will not—quit using carbon-based fuels at any time in the near future for a simple reason: they provide the horsepower that we crave. The hard reality is that oil, coal, and natural gas are here to stay.Fueling our society requires more than sentiment and rhetoric; we need to make good decisions and smart investments based on facts. In Power Hungry, Bryce provides a supertanker-load of footnoted facts while shepherding readers through basic physics and math. And with the help of a panoply of vivid graphics and tables, he crushes a phalanx of energy myths, showing why renewables are not green, carbon capture and sequestration won’t work, and even—surprise!—that the U.S. is leading the world in energy efficiency. He also charts the amazing growth of the fuels of the future: natural gas and nuclear.Power Hungry delivers a clear-eyed view of what America has “in the tank,” and what’s needed to transform the gargantuan global energy sector.

     Determined to secure a quick, decisive victory on the World War II battlefields, Adolf Hitler adopted an attack plan that combined tools with technique- the formidable Panzer divisions. Self-contained armored units able to operate independently, the Panzers became the German army's fighting core as well as its moral focus, establishing an entirely new military doctrine. In Hitler's Panzers, renowned World War II scholar Dennis Showalter presents a comprehensive and unbiased study of Nazi Germany's armored forces. By delving deeply into a detailed history of the theory, strategy, myths, and realities of Germany's technologically innovative approach to warfare, Showalter provides a look at the military lessons of the past, and a speculation on how the Panzer ethos may be implemented in the future of international conflict.

    This friendly-and-straightforward guide introduces the basics of electronics and enhances your learning experience by debunking and explaining concepts such as circuits, analog and digital, schematics, voltage, safety concerns, and more. Packed with nearly 900 pages of detailed information, this book shows you how to develop your own breadboard, design your own circuit, and get savvy with schematics. Covers the basics of electronics and demystifies a variety of electronics conceptsEncourages you to dive in and design a variety of fun and interesting entertainment electronics, mobile, and automotive projectsOffers troubleshooting advice for common electronics challengesReviews circuits, schematics, voltage, safety concerns, and much moreSo, get plugged in and start your next electronics project today with this book by your side!

    It is impossible to understand the spread of an epidemic, a computer virus, large-scale blackouts, or massive extinctions without taking into account the network structure that underlies all these phenomena. In this Very Short Introduction, Guido Caldarelli and Michele Catanzaro discuss the nature and variety of networks, using everyday examples from society, technology, nature, and history to explain and understand the science of network theory. They show the ubiquitous role of networks; how networks self-organize; why the rich get richer; and how networks can spontaneously collapse. They conclude by highlighting how the findings of complex network theory have very wide and important applications in genetics, ecology, communications, economics, and sociology.

    Lewis Carroll’s Symbolic logic : part I, Elementary, 1896, fifth edition, part II, Advanced, never previously published : together with letters from Lewis Carroll to eminent nineteenth-century logicians and to his "logical sister," and eight versions of the Barber-shop paradox / edited, with annotations and an introd., by William Warren Bartley, III.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    The consequences of this gathering may be enormous. In this new ebook, experts Patrick J. Michaels and Paul C. Knappenberger assess the issues sure to drive the debate before, during, and after the Paris meeting.

    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

    Enhancements to this edition include a more thorough coverage of transport processes, plus new or expanded coverage of separation process applications, fluidized beds, non-Newtonian fluids, membrane separation processes and gas-membrane theory, and much more. The book contains 240+ example problems and 550+ homework problems.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    Discover the “hidden gold” in Python’s standard library and start writing clean and Pythonic code today. Who Should Read This Book: If you’re wondering which lesser known parts in Python you should know about, you’ll get a roadmap with this book. Discover cool (yet practical!) Python tricks and blow your coworkers’ minds in your next code review. If you’ve got experience with legacy versions of Python, the book will get you up to speed with modern patterns and features introduced in Python 3 and backported to Python 2. If you’ve worked with other programming languages and you want to get up to speed with Python, you’ll pick up the idioms and practical tips you need to become a confident and effective Pythonista. If you want to make Python your own and learn how to write clean and Pythonic code, you’ll discover best practices and little-known tricks to round out your knowledge. What Python Developers Say About The Book: "I kept thinking that I wished I had access to a book like this when I started learning Python many years ago." — Mariatta Wijaya, Python Core Developer"This book makes you write better Python code!" — Bob Belderbos, Software Developer at Oracle"Far from being just a shallow collection of snippets, this book will leave the attentive reader with a deeper understanding of the inner workings of Python as well as an appreciation for its beauty." — Ben Felder, Pythonista"It's like having a seasoned tutor explaining, well, tricks!" — Daniel Meyer, Sr. Desktop Administrator at Tesla Inc.

    Then, attempting to break a Nazi code during World War II, he successfully designed and built one, thus ensuring the Allied victory. Turing became a champion of artificial intelligence, but his work was cut short. As an openly gay man at a time when homosexuality was illegal in England, he was convicted and forced to undergo a humiliating "treatment" that may have led to his suicide.With a novelist's sensitivity, David Leavitt portrays Turing in all his humanity—his eccentricities, his brilliance, his fatal candor—and elegantly explains his work and its implications.

    It quickly covers the essentials, and then focuses on the how-to instead of theory. It covers:Fundamental concepts such as circuits, schematics, voltage, safety, and more Tools of the trade, including multimeters, oscilloscopes, logic probes, and more Common electronic components (e.g. resistors, capacitors, transistors) Making circuits using breadboards and printed circuit boards Microcontrollers (implementation and programming) Author Gordon McComb has more than a million copies of his books in print, including his bestselling Robot Builder's Bonanza and VCRs and Camcorders For Dummies. He really connects with readers! With lots of photos and step-by-step explanations, this book will have you connecting electronic components in no time! In fact, it includes fun ideas for great projects you can build in 30 minutes or less. You'll be amazed! Then you can tackle cool robot projects that will amaze your friends! (The book gives you lots to choose from.)Students will find this a great reference and supplement to the typical dry, dull textbook. So whether you just want to bone up on electronics or want to get things hooked up, souped up, or fixed up, ...whether you're interested in fixing old electronic equipment, understanding guitar fuzz amps, or tinkering with robots, Electronics For Dummies is your quick connection to the stuff you need to know.