Boyd for the world of business.The success of Robert Coram's monumental biography, Boyd, the Fighter Pilot Who Changed the Art of War, rekindled interest in this obscure pilot and documented his influence on military matters ranging from his early work on fighter tactics to the USMC's maneuver warfare doctrine to the planning for Operation Desert Storm. Unfortunately Boyd's written legacy, consisting of a single paper and a four-set cycle of briefings, addresses strategy only in war. Boyd and BusinessBoyd did study business. He read everything he could find on the Toyota Production System and came to consider it as an implementation of ideas similar to his own. He took business into account when he formulated the final version of his OODA loop and in his last major briefing, Conceptual Spiral, on science and technology. He read and commented on early versions of this manuscript, but he never wrote on how business could operate more profitably by using his ideas.Other writers and business strategists have taken up the challenge, introducing Boyd's concepts and suggesting applications to business. Keith Hammonds, in the magazine Fast Company, George Stalk and Tom Hout in Competing Against Time, and Tom Peters most recently in Re-imagine! have described the OODA loop and its effects on competitors.They made significant contributions. Successful businesses, though, don t concentrate on affecting competitors but on enticing customers. You could apply Boyd all you wanted to competitors, but unless this somehow caused customers to buy your products and services, you ve wasted time and money. If this were all there were to Boyd, he would rate at most a sidebar in business strategy.Business is not WarPart of the problem has been Boyd's focus on war, where affecting competitors is the whole idea. Armed conflict was Boyd's life for nearly 50 years, first as a fighter pilot, then as a tactician and an instructor of fighter pilots, and after his retirement, as a military philosopher. Coram describes (and I know from personal experience) how his quest consumed Boyd virtually every waking hour.It was not a monastic existence, though, since John was above everything else a competitor and loved to argue over beer and cigars far into the night. During most of the 1970s and 80s he worked at the Pentagon, where he could share ideas and debate with other strategists and practitioners of the art of war. The result was the remarkable synthesis we know as Patterns of Conflict. Discussions about generals and campaigns, however, did not give Boyd much insight into competition in other areas, like businessNow you might expect, at first glance, that business is so much like war that lifting concepts from one and applying them to the other would be straightforward. But think about that for a minute. Even in its simplest description, business doesn't really look much like war. For one thing, there are always three sides to business competition: you, customers, and competitors. Often it is vastly more complex, with a multitude of competitors who are customers of each other as well. In business, unlike war, it may even be desirable to be conquered by a competitor in a lucrative merger or acquisition. Finally, and most important, it is rarely possible to defeat the other player in the triangle, that is, to compel an unwilling customer to buy. Attempts to pressure customers into paying too much or into buying more than they need often open a window for competitors (as the US airline industry is belatedly discovering.) Generally all we can do is attract offer products and services to potential customers, whose decisions determine who wins and who loses.What this means is that the strategies and tactics of war, Boyd's included, are destructive in nature and so never apply to business. Expressions like Attack enemy weaknesses have no meaning, except as metaphors and analogies. Across different domains, such literary devices are as likely to be misleading as helpful.Boyd's Strategy Still AppliesBusiness is not war, but it is a form of conflict, a situation where one group can win only if another group loses. If you dig beneath Boyd's war-centered tactics you find a general strategy for ensuring that in most any type of conflict your group will be the one that wins.Although Boyd made a number of new and fundamental contributions, his is an ancient school, extending back in written form 2,500 years. It is built around two primary themes:A focus on time (not speed) and specifically, using dislocations in time to shape the competitive situation. These effects, by the way, are quite different in business than they are in war.A culture with attributes that enable even impel organizations to exploit time for competitive advantage. Within Boyd's culture, members will seek out or invent specific practices that will work for it.Why You Should Read this BookThis book will give you a firm foundation in Boyd's strategy, starting with its military roots, but it is not a how-to manual. There could never be such a manual for strategy since all sides could use it and so would derive no strategic benefit. Anything you can write a how-to manual for is tactics or even technique. Strategy begins where these leave off.You should read this book if you ve found other books on business strategy lacking something. You should read it if you appreciate that Sun Tzu seems to be revealing fundamental truths, but it's not clear what they have to do with business. You should read it if you intend to run your own show without the decision making by committee, shunning of responsibility, and breakdown of ethics and trust that you see around you every day.

    The Apollo moon landing of 1961 was one of those events—the invention of the Apple personal computer was another. In this book, John Sculley—former CEO of both Pepsi and Apple—claims we are in an era that is giving birth to numerous groundbreaking events and inventions—moonshots—that will change the way we live and work for generations to come. The time is ripe, according to Sculley, for a new breed of innovative entrepreneurs to build businesses across industries that will bring in billions of dollars—while changing people’s lives for the better. And in this book, he’ll show you how to do it. Moonshot! lays out a roadmap for building a truly transformative business, beginning with a can’t-fail concept and drawing on clear examples from companies who’ve done innovation right.

    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

    Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, Complex Adaptive Systems focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.

    This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics--particularly in machine learning, scientific modeling, and artificial life--and reviews a broad span of research, including the work of Mitchell and her colleagues.The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting general purpose nature of genetic algorithms as search methods that can be employed across disciplines.An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.

    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.

    In his grey suit and tie, he looked like any other Soviet citizen. The bag alone was mildly conspicuous, printed with the red logo of Safeway, the British supermarket.The man was a spy for MI6. A senior KGB officer, for more than a decade he had supplied his British spymasters with a stream of priceless secrets from deep within the Soviet intelligence machine. No spy had done more to damage the KGB. The Safeway bag was a signal: to activate his escape plan to be smuggled out of Soviet Russia. So began one of the boldest and most extraordinary episodes in the history of spying. Ben Macintyre reveals a tale of espionage, betrayal and raw courage that changed the course of the Cold War forever...

    So why should larger, more established companies take notice? Because they have everything to gain when they examine and adopt the strategies, tools, and attitudes of these smaller competitors. The Lean Enterprise presents a groundbreaking design for revolutionizing larger organizations, one that draws on the ingenious tenets and practices espoused by the startup community. The guidelines in this book will help companies shake the lethargy, bureaucracy, and power struggles that plague large organizations and hold them back from true innovation.At the heart of this resource is a comprehensive, practical approach based on methods, timetables, compensation, financial investment, and case studies that reveal the startup mentality. Respected thought leaders in lean startup methodologies, the authors cover successful enterprise development, development innovation labs, corporate venture arms, and acquisition and integration of startups.- Essential reading for entrepreneurs, product managers, executives and directors in Forbes 2000 organizations, and board members- Presents the tools and methodologies large businesses need to compete with a new generation of highly-empowered entrepreneurs- Covers lean startup culture and principles and identifies the behaviors that arestunting growth at large enterprises- Offers a comprehensive, practical approach for developing exciting products and services and opening vast new marketsDon't be mystified by the success of startups. Master the methods of this new generation of entrepreneurs and compete on a level playing field.

    Army and Navy and the British government over the last five years. Now, Battle of Wits presents the history of the war that these documents reveal. From the battle of Midway until the last German code was broken in January 1945, this is an astonishing epic of a war that was won not simply by brute strength but also by reading the enemy's intentions. The revelations of Stephen Budiansky's dramatic history include how Britain tried to manipulate the American codebreakers and monopolize German Enigma code communications; the first detailed published explanations of how the Japanese codes were broken; and how the American codebreaking machines worked to crack the Japanese, the German, and even the Russian diplomatic codes. The compelling narrative shows the crucial effect codebreaking had on the battlefields by explaining the urgency of stopping the wolf pack U-boat attacks in the North Atlantic, the importance of halting Rommel's tanks in North Africa, and the necessity of ensuring that the Germans believed the Allies' audacious deception and cover plans for D-Day. Unveiled for the first time, the complete story of codebreaking in World War II has now been told.

    In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice.This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises.This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective.

    In this book, he shares his methods in great detail. Each step of his process is explained throughout twenty-five chapters of specialized websites, software solutions, and creative search techniques. Over 250 resources are identified with narrative tutorials and screen captures. This book will serve as a reference guide for anyone that is responsible for the collection of online content. It is written in a hands-on style that encourages the reader to execute the tutorials as they go. The search techniques offered will inspire analysts to "think outside the box" when scouring the internet for personal information. Much of the content of this book has never been discussed in any publication. Always thinking like a hacker, the author has identified new ways to use various technologies for an unintended purpose. This book will greatly improve anyone's online investigative skills. Among other techniques, you will learn how to locate: Hidden Social Network Content Cell Phone Subscriber Information Deleted Websites & Posts Missing Facebook Profile Data Full Twitter Account Data Alias Social Network Profiles Free Investigative Software Useful Browser Extensions Alternative Search Engine Results Website Owner Information Photo GPS & Metadata Live Streaming Social Content Social Content by Location IP Addresses of Users Additional User Accounts Sensitive Documents & Photos Private Email Addresses Duplicate Video Posts Mobile App Network Data Unlisted Addresses s Public Government Records Document Metadata Rental Vehicle Contracts Online Criminal Activity Personal Radio Communications Compromised Email Information Automated Collection Solutions Linux Investigative Programs Dark Web Content (Tor) Restricted YouTube Content Hidden Website Details Vehicle Registration Details

    The blades start moving in 60 seconds. What do you do? If you want to work at Google, or any of America's best companies, you need to have an answer to this and other puzzling questions. Are You Smart Enough to Work at Google? guides readers through the surprising solutions to dozens of the most challenging interview questions. The book covers the importance of creative thinking, ways to get a leg up on the competition, what your Facebook page says about you, and much more. Are You Smart Enough to Work at Google? is a must-read for anyone who wants to succeed in today's job market.

    The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout. Author resource page: http: //www.stat.columbia.edu/ gelman/arm/

    We put out fires. We deal with emergencies. We stay downstream, handling one problem after another, but we never make our way upstream to fix the systems that caused the problems ... [This book] probes the psychological forces that push us downstream--including 'problem blindness,' which can leave us oblivious to serious problems in our midst. And Heath introduces us to the thinkers who have overcome these obstacles and scored ... victories by switching to an upstream mindset.

    However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.