It’s no coincidence that geniuses not only dare to dream of the impossible for their work, but do the same for their lives. They’re audacious enough to think that they’re not just ordinary players. Few stories better illustrate this better than the life of the father of the modern world, a man of legendary imaginative power and wonder: Nikola Tesla.In this book, you’ll be taken on a whirlwind journey through Tesla’s life and work, and not only learn about the successes and mistakes of one of history’s greatest inventors, but also how to look at the world in a different, more imaginative way.Read this book now and learn lessons from Nikola Tesla on why imagination is so vital to awakening your inner genius, and insights into the real “secret” to creativity, as explained by people like Jobs, Picasso, Dali, and Twain.

    Mitnick claims that this socialengineering tactic was the single-most effective method in hisarsenal. This indispensable book examines a variety of maneuversthat are aimed at deceiving unsuspecting victims, while it alsoaddresses ways to prevent social engineering threats.Examines social engineering, the science of influencing atarget to perform a desired task or divulge informationArms you with invaluable information about the many methods oftrickery that hackers use in order to gather information with theintent of executing identity theft, fraud, or gaining computersystem accessReveals vital steps for preventing social engineeringthreatsSocial Engineering: The Art of Human Hacking does itspart to prepare you against nefarious hackers--now you can doyour part by putting to good use the critical information withinits pages.

    While this has had the positive effect of equalizing access to knowledge, it also has lowered the bar on what depth of knowledge is required to consider oneself an "expert." A cult of anti-expertise sentiment has coincided with anti-intellectualism, resulting in massively viral yet poorly informed debates ranging from the anti-vaccination movement to attacks on GMOs. This surge in intellectual egalitarianism has altered the landscape of debates-all voices are equal, and "fact" is a subjective term. Browsing WebMD puts one on equal footing with doctors, and Wikipedia allows all to be foreign policy experts, scientists, and more. As Tom Nichols shows in The Death of Expertise, there are a number of reasons why this has occurred-ranging from easy access to Internet search engines to a customer satisfaction model within higher education. The product of these interrelated trends, Nichols argues, is a pervasive distrust of expertise among the public coinciding with an unfounded belief among non-experts that their opinions should have equal standing with those of the experts. The experts are not always right, of course, and Nichols discusses expert failure. The crucial point is that bad decisions by experts can and have been effectively challenged by other well-informed experts. The issue now is that the democratization of information dissemination has created an army of ill-informed citizens who denounce expertise.When challenged, non-experts resort to the false argument that the experts are often wrong. Though it may be true, but the solution is not to jettison expertise as an ideal; it is to improve our expertise. Nichols is certainly not opposed to information democratization, but rather the enlightenment people believe they achieve after superficial internet research. He shows in vivid detail the ways in which this impulse is coursing through our culture and body politic, but the larger goal is to explain the benefits that expertise and rigorous learning regimes bestow upon all societies.

    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

    Robert Gibbons addresses scholars in applied fields within economics who want a serious and thorough discussion of game theory but who may have found other works overly abstract. Gibbons emphasizes the economic applications of the theory at least as much as the pure theory itself; formal arguments about abstract games play a minor role. The applications illustrate the process of model building--of translating an informal description of a multi-person decision situation into a formal game-theoretic problem to be analyzed. Also, the variety of applications shows that similar issues arise in different areas of economics, and that the same game-theoretic tools can be applied in each setting. In order to emphasize the broad potential scope of the theory, conventional applications from industrial organization have been largely replaced by applications from labor, macro, and other applied fields in economics. The book covers four classes of games, and four corresponding notions of equilibrium: static games of complete information and Nash equilibrium, dynamic games of complete information and subgame-perfect Nash equilibrium, static games of incomplete information and Bayesian Nash equilibrium, and dynamic games of incomplete information and perfect Bayesian equilibrium.

    While many of the mathematicians and software engineers on Wall Street failed when their abstractions turned ugly in practice, a special breed of physicists has a much deeper history of revolutionizing finance. Taking us from fin-de-siècle Paris to Rat Pack-era Las Vegas, from wartime government labs to Yippie communes on the Pacific coast, Weatherall shows how physicists successfully brought their science to bear on some of the thorniest problems in economics, from options pricing to bubbles.The crisis was partly a failure of mathematical modeling. But even more, it was a failure of some very sophisticated financial institutions to think like physicists. Models—whether in science or finance—have limitations; they break down under certain conditions. And in 2008, sophisticated models fell into the hands of people who didn’t understand their purpose, and didn’t care. It was a catastrophic misuse of science.The solution, however, is not to give up on models; it's to make them better. Weatherall reveals the people and ideas on the cusp of a new era in finance. We see a geophysicist use a model designed for earthquakes to predict a massive stock market crash. We discover a physicist-run hedge fund that earned 2,478.6% over the course of the 1990s. And we see how an obscure idea from quantum theory might soon be used to create a far more accurate Consumer Price Index.Both persuasive and accessible, The Physics of Wall Street is riveting history that will change how we think about our economic future.

    In it, developer and life coach John Sonmez addresses a wide range of important "soft" topics, from career and productivity to personal finance and investing, and even fitness and relationships, all from a developer-centric viewpoint.For most software developers, coding is the fun part. The hard bits are dealing with clients, peers, and managers, staying productive, achieving financial security, keeping yourself in shape, and finding true love. This book is here to help.Soft Skills: The software developer's life manual is a guide to a well-rounded, satisfying life as a technology professional. In it, developer and life coach John Sonmez offers advice to developers on important "soft" subjects like career and productivity, personal finance and investing, and even fitness and relationships. Arranged as a collection of 71 short chapters, this fun-to-read book invites you to dip in wherever you like. A Taking Action section at the end of each chapter shows you how to get quick results. Soft Skills will help make you a better programmer, a more valuable employee, and a happier, healthier person.What's InsideBoost your career by building a personal brandJohn's secret ten-step process for learning quicklyFitness advice to turn your geekiness to your advantageUnique strategies for investment and early retirement

    50 Great Myths of Popular Psychology uses popular myths as a vehicle for helping students and laypersons to distinguish science from pseudoscience.# Uses common myths as a vehicle for exploring how to distinguish factual from fictional claims in popular psychology# Explores topics that readers will relate to, but often misunderstand, such as 'opposites attract', 'people use only 10% of their brains', and 'handwriting reveals your personality'# Provides a 'mythbusting kit' for evaluating folk psychology claims in everyday life# Teaches essential critical thinking skills through detailed discussions of each myth# Includes over 200 additional psychological myths for readers to explore# Contains an Appendix of useful Web Sites for examining psychological myths# Features a postscript of remarkable psychological findings that sound like myths but that are true# Engaging and accessible writing style that appeals to students and lay readers alike

    Because the information in the unconscious is in an unruly and often disturbing form, a "censor" in the preconscious will not allow it to pass unaltered into the conscious. During dreams, the preconscious is more lax in this duty than in waking hours, but is still attentive: as such, the unconscious must distort and warp the meaning of its information to make it through the censorship. As such, images in dreams are often not what they appear to be, according to Freud, and need deeper interpretation if they are to inform on the structures of the unconscious.

    More than a series of fascinating case studies, To Engineer Is Human is a work that looks at our deepest notions of progress and perfection, tracing the fine connection between the quantifiable realm of science and the chaotic realities of everyday life."Alert, inquisitive, unspecialized, wholly human...refreshingly eclectic." --The Spectator"Henry Petroski is an ardent engineer, and if he writes more good books like this, he might find himself nominated to become the meistersinger of the guild. [This is] a refreshing plunge into the dynamics of the engineering ethos...as straightforward as an I-beam."--Science

    Edited by the Sustainability Institute’s Diana Wright, this essential primer brings systems thinking out of the realm of computers and equations and into the tangible world, showing readers how to develop the systems-thinking skills that thought leaders across the globe consider critical for 21st-century life.Some of the biggest problems facing the world—war, hunger, poverty, and environmental degradation—are essentially system failures. They cannot be solved by fixing one piece in isolation from the others, because even seemingly minor details have enormous power to undermine the best efforts of too-narrow thinking.While readers will learn the conceptual tools and methods of systems thinking, the heart of the book is grander than methodology. Donella Meadows was known as much for nurturing positive outcomes as she was for delving into the science behind global dilemmas. She reminds readers to pay attention to what is important, not just what is quantifiable, to stay humble, and to stay a learner.In a world growing ever more complicated, crowded, and interdependent, Thinking in Systems helps readers avoid confusion and helplessness, the first step toward finding proactive and effective solutions.

    Whether you are a student, software developer, tech entrepreneur, or researcher in computer science, this authoritative and self-contained book tells you everything you need to know about the new global money for the Internet age.How do Bitcoin and its block chain actually work? How secure are your bitcoins? How anonymous are their users? Can cryptocurrencies be regulated? These are some of the many questions this book answers. It begins by tracing the history and development of Bitcoin and cryptocurrencies, and then gives the conceptual and practical foundations you need to engineer secure software that interacts with the Bitcoin network as well as to integrate ideas from Bitcoin into your own projects. Topics include decentralization, mining, the politics of Bitcoin, altcoins and the cryptocurrency ecosystem, the future of Bitcoin, and more.An essential introduction to the new technologies of digital currencyCovers the history and mechanics of Bitcoin and the block chain, security, decentralization, anonymity, politics and regulation, altcoins, and much moreFeatures an accompanying website that includes instructional videos for each chapter, homework problems, programming assignments, and lecture slidesAlso suitable for use with the authors' Coursera online courseElectronic solutions manual (available only to professors)

     The more tools you have at your disposal, the more likely you'll use the right tool for the job — and get it done right. The same is true when it comes to your thinking. The quality of your outcomes depends on the mental models in your head. And most people are going through life with little more than a hammer. Until now. The Great Mental Models: General Thinking Concepts is the first book in The Great Mental Models series designed to upgrade your thinking with the best, most useful and powerful tools so you always have the right one on hand. This volume details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making, productivity, and how clearly you see the world. You will discover what forces govern the universe and how to focus your efforts so you can harness them to your advantage, rather than fight with them or worse yet— ignore them. Upgrade your mental toolbox and get the first volume today!

    But developing these systems brings its own set of headaches. With lots of examples and practical advice, this book takes a holistic view of the topics that system architects and administrators must consider when building, managing, and evolving microservice architectures.Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You'll follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain.Discover how microservices allow you to align your system design with your organization's goalsLearn options for integrating a service with the rest of your systemTake an incremental approach when splitting monolithic codebasesDeploy individual microservices through continuous integrationExamine the complexities of testing and monitoring distributed servicesManage security with user-to-service and service-to-service modelsUnderstand the challenges of scaling microservice architectures

    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.