This book addresses questions such as: can we define technology? Does technology shape us, or do we shape it? Is technology inevitable or unpredictable?

    Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of exercises, case studies, and easy-to-understand explanations.You’ll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise.Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tablesStudy abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machinesGet starter code and solutions to help you re-implement and extend original experiments in complexityExplore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topicsExamine case studies of complex systems submitted by students and readers

    GIFT BOX SET OF 4 BOOKS TITLED: THE PUPPET MASTERS - ISBN 0345330145, WALDO&MAGIC - ISBN 0345330153, DOUBLE STAR - ISBN 0345330137 AND THE DOOR INTO SUMMER - ISBN 0345330129

    Indeed, if God knows everything, why do we need to learn through pain and suffering? If God is omnipotent, why are we needed to do good? If the universe is fundamentally good, why are wars, crime, and injustice all around us? In modern society, orthodox science takes the rational high-ground and tackles these contradictions by denying the very need for, and the existence of, meaning. Indeed, many of us implicitly accept the notion that rationality somehow contradicts spirituality. That is a modern human tragedy, not only for its insidiousness, but for the fact that it is simply not true. In this book, the author constructs a coherent and logical argument for the meaning of existence, informed by science itself. A framework is laid out wherein all aspects of human existence have a logical, coherent reason and role, including the ones often perceived as negative. The powerful logic of this framework inescapably leads to insightful and inspiring guidelines for living a purposeful and meaningful life.

    It emphasizes forms suitable for students and researchers whose interest lies in solving equations rather than in general theory. Solutions to odd-numbered problems appear at the end. 1957 edition.

    For centuries, the power of zero savored of the demonic; once harnessed, it became the most important tool in mathematics. Zero follows this number from its birth as an Eastern philosophical concept to its struggle for acceptance in Europe and its apotheosis as the mystery of the black hole. Today, zero lies at the heart of one of the biggest scientific controversies of all time, the quest for the theory of everything. Elegant, witty, and enlightening, Zero is a compelling look at the strangest number in the universe and one of the greatest paradoxes of human thought.

    The calculus is not a hard subject and I prove this through an easy to read and obvious approach spanning only 100 pages. I have written this book with the following type of student in mind; the non-traditional student returning to college after a long break, a notoriously weak student in math who just needs to get past calculus to obtain a degree, and the garage tinkerer who wishes to understand a little more about the technical subjects. This book is meant to address the many fundamental thought-blocks that keep the average 'mathaphobe' (or just an interested person who doesn't have the time to enroll in a course) from excelling in mathematics in a clear and concise manner. It is my sincerest hope that this book helps you with your needs.Show more Show less

    Bernard Haisch contends that there is a purpose and an underlying intelligence behind the Universe, one that is consistent with modern science, especially the Big Bang and evolution. It is based on recent discoveries that there are numerous coincidences and fine-tunings of the laws of nature that seem extraordinarily unlikely.A more rational concept of God is called for. As astrophysicist Sir James Jeans wrote, "the Universe begins to look more like a great thought than like a great machine."Despite bestsellers by Christopher Hitchens, Richard Dawkins, and Sam Harris that have denounced the evils of religion and proclaimed that science has shown that there is no God, The Purpose-Guided Universe shows how one can believe in God and science.

    Worked examples and exercises support the text. An ELBS/LPBB edition is available.

    With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora

    From the classroom to the courtroom and from financial markets to supermarkets, Mlodinow's intriguing and illuminating look at how randomness, chance, and probability affect our daily lives will intrigue, awe, and inspire.

    This seems to have been the case even from the first recognition of the Neanderthals as a species. The first Neanderthal fossil discovery was that of a child’s skull in Belgium in 1829, but it was badly damaged. Another would be discovered in 1856 in a limestone mine of the Neanderthal region of what is present-day Germany, and a skull with differing distinct traits (indicating a different species than the Neanderthals) would be discovered just over a decade later in southwestern France. The latter specimen would come to be recognized as an example of the species Homo Sapiens, and these anatomically modern humans arrived in Europe between 45,000 and 43,000 years ago, around the time the Neanderthals are believed to started going extinct. The Neanderthals are a member of the genus Homo just like Homo sapiens and share roughly 99.7% of their DNA with modern humans (Reynolds and Gallagher 2012). Both species even lived briefly during the same time in Eurasia. However, the Neanderthals evolved separately in Europe, away from modern humans, who evolved in Africa. Physically, the Neanderthal skeleton was much more robust, suggesting that there was more room for muscle attachment. However, while Neanderthals were stronger than modern humans, the average height of the Neanderthal male was shorter, standing at only about 5’5 tall. Other physical characteristics that set the Neanderthals apart from modern humans were certain skull traits. The skull in general was low and elongated, featuring a sloping forehead with an occipital bun (a bone projection at the back of the skull), whereas modern humans have a more vertical forehead with no occipital bun. The cranial capacity of the Neanderthal skull was also greater than the modern human at 1,500–1,740 cc, and it lacked a chin and had more circular eye orbits, in contrast to Homo sapiens, which have a chin and tend to feature more rectangular eye orbits (Wolpoff 1999). Despite these differences, the Neanderthals may have been recognizable enough to interact with Homo sapiens or even blend in with Homo sapiens for the thousands of years they lived together in Europe. The Neanderthals lived in Europe and Asia for nearly 200,000 years and thrived in these regions, but they went extinct between 40,000 and 30,000 years ago, around the same time that modern humans began arriving in Europe. This has prompted much speculation as to the nature of the interactions between Neanderthals and Homo sapiens, especially since some researchers believe they interacted with each other for over 5,000 years before the Neanderthals began going extinct at different times across Europe. One hypothesis is that Homo sapiens displaced the Neanderthals and were better suited for the environment, and it is obviously possible if not likely that these two groups had become competitors for food and other resources, with Homo sapiens being more successful in the end. If such close interactions were taking place, there is also a possibility that the relatively new-to-Europe Homo sapiens brought pathogens from Africa with them that were unknown to the Neanderthal’s immune system. A more recent example of this type of resulting interaction is the European expansion into the Americas, which brought diseases like smallpox that the natives of America had never experienced before, especially diseases resulting from the domestication of animals. It is possible that the domestication of the dog by Homo sapiens may have contributed in spreading foreign diseases among the Neanderthals.

    Now he brings his considerable talents to the history of one of math's most enduring puzzles: the seemingly paradoxical nature of infinity.Is infinity a valid mathematical property or a meaningless abstraction? The nineteenth-century mathematical genius Georg Cantor's answer to this question not only surprised him but also shook the very foundations upon which math had been built. Cantor's counterintuitive discovery of a progression of larger and larger infinities created controversy in his time and may have hastened his mental breakdown, but it also helped lead to the development of set theory, analytic philosophy, and even computer technology.Smart, challenging, and thoroughly rewarding, Wallace's tour de force brings immediate and high-profile recognition to the bizarre and fascinating world of higher mathematics.

    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.

    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.