They regale readers with riveting vignettes of how AIG grew from a modest group of insurance enterprises in 1970 to the largest insurance company in world history. They help us understand AIG's distinctive entrepreneurial culture and how its outstanding employees worldwide helped pave the road to globalization.Corrects numerous common misconceptions about AIG that arose due to its role at the center of the financial crisis of 2008. A unique account of AIG by one of the iconic business leaders of the twentieth century who developed close relationships with many of the most important world leaders of the period and helped to open markets everywhere Offers new critical perspective on battles with N. Y. Attorney General Eliot Spitzer and the 2008 U.S. government seizure of AIG amid the financial crisis Shares considerable information not previously made public The AIG Story captures an impressive saga in business history--one of innovation, vision and leadership at a company that was nearly--destroyed with a few strokes of governmental pens. The AIG Story carries important lessons and implications for the U.S., especially its role in international affairs, its approach to business, its legal system and its handling of financial crises.

    But building a machine learning system requires that you make practical decisions: Should you collect more training data? Should you use end-to-end deep learning? How do you deal with your training set not matching your test set? and many more. Historically, the only way to learn how to make these "strategy" decisions has been a multi-year apprenticeship in a graduate program or company. This is a book to help you quickly gain this skill, so that you can become better at building AI systems.

      “An unexpectedly intimate look into a highly accomplished man, his colleagues and friends, the development of a new field of geometric analysis, and a glimpse into a truly uncommon mind.”—Nina MacLaughlin, Boston Globe “Engaging, eminently readable . . . For those with a taste for elegant and largely jargon-free explanations of mathematics, The Shape of a Life promises hours of rewarding reading.”—Judith Goodstein, American Scientist  Harvard geometer and Fields medalist Shing-Tung Yau has provided a mathematical foundation for string theory, offered new insights into black holes, and mathematically demonstrated the stability of our universe. In this autobiography, Yau reflects on his improbable journey to becoming one of the world’s most distinguished mathematicians. Beginning with an impoverished childhood in China and Hong Kong, Yau takes readers through his doctoral studies at Berkeley during the height of the Vietnam War protests, his Fields Medal–winning proof of the Calabi conjecture, his return to China, and his pioneering work in geometric analysis. This new branch of geometry, which Yau built up with his friends and colleagues, has paved the way for solutions to several important and previously intransigent problems. With complicated ideas explained for a broad audience, this book offers readers not only insights into the life of an eminent mathematician, but also an accessible way to understand advanced and highly abstract concepts in mathematics and theoretical physics.

    Cash games were rarely spread in conventional poker rooms, let alone the Internet. All of that changed when the game exploded on television. No-limit cash games started sprouting up at casinos of all types. No-limit hold em is now the most popular form of poker. Tournaments pushed it to the forefront, and a great deal of money can also be won here despite that fact, many players feel frustrated with their results. They win some money, only to lose it all on one botched hand. This book teaches you how to play and think like a professional. It shows how to size your bets, manage the pot, manipulate your opponents, know when to go all-in, and avoid the big mistake. Do you understand critical no-limit concepts like The REM Process, The Commitment Threshold, and Stack-To-Pot Ratios? If not, this is the book for you.

    Techniques covered include state- and goal-based behavior, inter-agent communication, individual and group steering behaviors, team AI, graph theory, search, path planning and optimization, triggers, scripting, scripted finite state machines, perceptual modeling, goal evaluation, goal arbitration, and fuzzy logic.

    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.

    In this simple pattern beginning with two ones, each succeeding number is the sum of the two numbers immediately preceding it (1, 1, 2, 3, 5, 8, 13, 21, ad infinitum). Far from being just a curiosity, this sequence recurs in structures found throughout nature - from the arrangement of whorls on a pinecone to the branches of certain plant stems. All of which is astounding evidence for the deep mathematical basis of the natural world. With admirable clarity, two veteran math educators take us on a fascinating tour of the many ramifications of the Fibonacci numbers. They begin with a brief history of a distinguished Italian discoverer, who, among other accomplishments, was responsible for popularizing the use of Arabic numerals in the West. Turning to botany, the authors demonstrate, through illustrative diagrams, the unbelievable connections between Fibonacci numbers and natural forms (pineapples, sunflowers, and daisies are just a few examples). In art, architecture, the stock market, and other areas of society and culture, they point out numerous examples of the Fibonacci sequence as well as its derivative, the "golden ratio." And of course in mathematics, as the authors amply demonstrate, there are almost boundless applications in probability, number theory, geometry, algebra, and Pascal's triangle, to name a few.Accessible and appealing to even the most math-phobic individual, this fun and enlightening book allows the reader to appreciate the elegance of mathematics and its amazing applications in both natural and cultural settings.

    Bleak tools of the cold war, they embodied the rigid organization and mechanical conformity that made the military-industrial complex possible. But by the 1990s—and the dawn of the Internet—computers started to represent a very different kind of world: a collaborative and digital utopia modeled on the communal ideals of the hippies who so vehemently rebelled against the cold war establishment in the first place. From Counterculture to Cyberculture is the first book to explore this extraordinary and ironic transformation. Fred Turner here traces the previously untold story of a highly influential group of San Francisco Bay–area entrepreneurs: Stewart Brand and the Whole Earth network. Between 1968 and 1998, via such familiar venues as the National Book Award–winning Whole Earth Catalog, the computer conferencing system known as WELL, and, ultimately, the launch of the wildly successful Wired magazine, Brand and his colleagues brokered a long-running collaboration between San Francisco flower power and the emerging technological hub of Silicon Valley. Thanks to their vision, counterculturalists and technologists alike joined together to reimagine computers as tools for personal liberation, the building of virtual and decidedly alternative communities, and the exploration of bold new social frontiers. Shedding new light on how our networked culture came to be, this fascinating book reminds us that the distance between the Grateful Dead and Google, between Ken Kesey and the computer itself, is not as great as we might think.

    Now, in an exciting, fast-paced historical narrative ranging across two centuries, Mark Ronan takes us on an exhilarating tour of this final mathematical quest. Ronan describes how the quest to understand symmetry really began with the tragic young genius Evariste Galois, who died at the age of 20 in a duel. Galois, who spent the night before he died frantically scribbling his unpublished discoveries, used symmetry to understand algebraic equations, and he discovered that there were building blocks or atoms of symmetry. Most of these building blocks fit into a table, rather like the periodic table of elements, but mathematicians have found 26 exceptions. The biggest of these was dubbed the Monster--a giant snowflake in 196,884 dimensions. Ronan, who personally knows the individuals now working on this problem, reveals how the Monster was only dimly seen at first. As more and more mathematicians became involved, the Monster became clearer, and it was found to be not monstrous but a beautiful form that pointed out deep connections between symmetry, string theory, and the very fabric and form of the universe. This story of discovery involves extraordinary characters, and Mark Ronan brings these people to life, vividly recreating the growing excitement of what became the biggest joint project ever in the field of mathematics. Vibrantly written, Symmetry and the Monster is a must-read for all fans of popular science--and especially readers of such books as Fermat's Last Theorem.

    The author of What Is the Name of This Book? presents a compilation of more than two hundred challenging new logic puzzles--ranging from simple brainteasers to complex mathematical paradoxes.

    The daughter of Lang Hancock – legendary arch-conservative, secessionist, mining millionaire and discoverer of the world's largest iron deposit in the Pilbara – Gina has grown up in a family known as much for its front-page legal stoushes as for its business acumen and toughness.With her reported wealth more than doubling in the last twelve months, Rinehart is beginning to flex the enormous power her money gives, buying large shareholdings in television's Ten Network and newspaper group Fairfax Media. They are moves that will give Rinehart and her controversial views a major place in Australian life and public affairs.Based on painstaking research and a wealth of interviews with Rinehart's colleagues, friends, family and former employees, award-winning journalist Adele Ferguson has written the definitive biography, shining a light into the private world of Gina Rinehart, her family, her feuds and the iron determination that has driven her relentless rise.

    Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.

    To mark the event, National Geographic magazine commissioned seven articles that explore the fascinating issues—including demographics, food security, climate change, fertility trends, managing biodiversity—surrounding this topic, which are collected for the first time in this special ebook.   Envi­ronment editor Robert Kunzig starts by sketching out a natural history of population. The issues associated with population growth seem endless: poverty, food and water supply, world health, climate change, deforestation, fertility rates, and more. In additional chapters Elizabeth Kolbert explores a new era—the “Anthropocene,” or the age of man—defined by our massive impact on the planet, which will endure long after our cities have crumbled; and takes us to the Mediterranean, where she delves into issues associated with increasing ocean acidification. In Bangladesh, Don Belt explores how the people of this crowded region can teach us about adapting to rising sea levels. In “Food Ark” we travel deep within the earth and around the globe to explore the seed banks that are preserving the variety of food species we may need to increase food production on an increasingly crowded planet. In Brazil, Cynthia Gournay explores the phenomenon of “Machisma” and shows how a mix of female empowerment and steamy soap operas helped bring down Brazil’s fertility rate and stoke its vibrant economy. Additionally we explore threats to biodiversity, and the return of cities—which may be the solution to many of our population woes. Join National Geographic on this incredible journey to explore our rapidly growing planet.

    Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges.It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.

    Linear algebra is tightly integrated into the text.