Therefore, this book provides the fundamental concepts and techniques of real analysis for readers in all of these areas. It helps one develop the ability to think deductively, analyze mathematical situations and extend ideas to a new context. Like the first two editions, this edition maintains the same spirit and user-friendly approach with some streamlined arguments, a few new examples, rearranged topics, and a new chapter on the Generalized Riemann Integral.

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    Sapolsky's acclaimed and successful Why Zebras Don't Get Ulcers features new chapters on how stress affects sleep and addiction, as well as new insights into anxiety and personality disorder and the impact of spirituality on managing stress.As Sapolsky explains, most of us do not lie awake at night worrying about whether we have leprosy or malaria. Instead, the diseases we fear--and the ones that plague us now--are illnesses brought on by the slow accumulation of damage, such as heart disease and cancer. When we worry or experience stress, our body turns on the same physiological responses that an animal's does, but we do not resolve conflict in the same way--through fighting or fleeing. Over time, this activation of a stress response makes us sick.

    With extensive treatment of the heart of epidemiology-from study designs to descriptive epidemiology to quantitative measures-this reader-friendly text is accessible and interesting to a wide range of beginning students in all health-related disciplines. A unique focus is given to real-world applications of epidemiology and the development of skills that students can apply in subsequent course work and in the field. The text is also accompanied by a complete package of instructor and student resources available through a companion Web site.

    Drawing on his breakthrough research in comparative neuroscience, Terrence Deacon offers a wealth of insights into the significance of symbolic thinking: from the co-evolutionary exchange between language and brains over two million years of hominid evolution to the ethical repercussions that followed man's newfound access to other people's thoughts and emotions.Informing these insights is a new understanding of how Darwinian processes underlie the brain's development and function as well as its evolution. In contrast to much contemporary neuroscience that treats the brain as no more or less than a computer, Deacon provides a new clarity of vision into the mechanism of mind. It injects a renewed sense of adventure into the experience of being human.

    Indeed, the brain's power is being confirmed every day in new studies and research. But there is a brain we don't generally hear about, a brain we might not want to hear about…the "prima donna within."Exposing the mind's deceptions and exploring how the mind defends and glorifies the ego, Dr. Cordelia Fine illustrates the brain's tendency to self-delusion. Whether it be hindsight bias, wishful thinking, unrealistic optimism, or moral excuse-making, each of us has a slew of inborn mind-bugs and ordinary prejudices that prevent us from seeing the truth about the world and ourselves. With fascinating studies to support her arguments, Dr. Fine takes us on an insightful, rip-roaringly funny tour through the brain you never knew you had.

    Scientists have long supported this assumption by claiming that emotions are hardwired in the body or the brain. Today, however, the science of emotion is in the midst of a revolution on par with the discovery of relativity in physics and natural selection in biology—ans this paradigm shift has far-reaching implications for us all.Leading the charge is psychologist and neuroscientist Lisa Feldman Barrett, whose theory of emotion is driving a deeper understanding of the mind and brain, and shedding new light on what it means to be human. Her research overturns the widely held belief that emotions are housed in different parts of the brain and are universally expressed and recognized. Instead, she has shown that emotion is constructed in the moment, by core systems that interact across the whole brain, aided by a lifetime of learning. This new theory means that you play a much greater role in your emotional life than you ever thought. Its repercussions are already shaking the foundations not only of psychology but also of medicine, the legal system, child-rearing, meditation, and even airport security.Why do emotions feel automatic? Does rational thought really control emotion? How does emotion affect disease? How can you make your children more emotionally intelligent? How Emotions Are Made answers these questions and many more, revealing the latest research and intriguing practical applications of the new science of emotion, mind, and brain.

    Distinguishing agents (e.g., molecules, cells, animals, and species) from their interactions (e.g., chemical reactions, immune system responses, sexual reproduction, and evolution), Flake argues that it is the computational properties of interactions that account for much of what we think of as beautiful and interesting. From this basic thesis, Flake explores what he considers to be today's four most interesting computational topics: fractals, chaos, complex systems, and adaptation.Each of the book's parts can be read independently, enabling even the casual reader to understand and work with the basic equations and programs. Yet the parts are bound together by the theme of the computer as a laboratory and a metaphor for understanding the universe. The inspired reader will experiment further with the ideas presented to create fractal landscapes, chaotic systems, artificial life forms, genetic algorithms, and artificial neural networks.

    The text relates the fundamentals to three real-world examples: Intel's 8085, Motorola's 6800, and the 6502 chip used by Apple Computers. This edition includes a student version of the TASM cross-assembler software program, experiments for Digital Computer Electronics and more.

    How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

    Increasingly, the decisions that affect our lives--where we go to school, whether we can get a job or a loan, how much we pay for health insurance--are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.But as mathematician and data scientist Cathy O'Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination--propping up the lucky, punishing the downtrodden, and undermining our democracy in the process.

    Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

    The presentation stresses analytical methods, concrete examples, and geometric intuition. A unique feature of the book is its emphasis on applications. These include mechanical vibrations, lasers, biological rhythms, superconducting circuits, insect outbreaks, chemical oscillators, genetic control systems, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with mathematical theory.About the Author:Steven Strogatz is in the Center for Applied Mathematics and the Department of Theoretical and Applied Mathematics at Cornell University. Since receiving his Ph.D. from Harvard university in 1986, Professor Strogatz has been honored with several awards, including the E.M. Baker Award for Excellence, the highest teaching award given by MIT.

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

    But what is the mind? What do we mean when we say we are "aware" of something? What is this peculiar state in our heads, at once utterly familiar and bewilderingly mysterious, that we call awareness or consciousness? In Physics in Mind, eminent biophysicist Werner R. Loewenstein argues that to answer these questions, we must first understand the physical mechanisms that underlie the workings of the mind. And so begins an exhilarating journey along the sensory data stream of the brain, which shows how our most complex organ processes the vast amounts of information coming in through our senses to create a coherent, meaningful picture of the world. Bringing information theory to bear on recent advances in the neurosciences, Loewenstein reveals a web of immense computational power inside the brain. He introduces the revolutionary idea that quantum mechanics could be fundamental to how our minds almost instantaneously deal with staggering amounts of information, as in the case of the information streaming through our eyes. Combining cutting-edge research in neuroscience and physics, Loewenstein presents an ambitious hypothesis about the parallel processing of sensory information that is the heart, hub, and pivot of the cognitive brain. Wide-ranging and brimming with insight, Physics in Mind breaks new ground in our understanding of how the mind works.