In 1996 Joseph LeDoux's "The Emotional Brain" presented a revelatory examination of the biological bases of our emotions and memories. Now, the world-renowned expert on the brain has produced with a groundbreaking work that tells a more profound story: how the little spaces between the neurons-the brain's synapses--are the channels through which we think, act, imagine, feel, and remember. Synapses encode the essence of personality, enabling each of us to function as a distinctive, integrated individual from moment to moment. Exploring the functioning of memory, the synaptic basis of mental illness and drug addiction, and the mechanism of self-awareness, "Synaptic Self" is a provocative and mind-expanding work that is destined to become a classic.

    With a new introduction, three new chapters, modernized language and methods throughout, and an appendix of challenging and enjoyable practice problems, Calculus Made Easy has been thoroughly updated for the modern reader.

    We nevertheless muddle through even in the absence of theories of how to act. But how do we do it?In Probably Approximately Correct, computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own. The key is “probably approximately correct” algorithms, a concept Valiant developed to explain how effective behavior can be learned. The model shows that pragmatically coping with a problem can provide a satisfactory solution in the absence of any theory of the problem. After all, finding a mate does not require a theory of mating. Valiant’s theory reveals the shared computational nature of evolution and learning, and sheds light on perennial questions such as nature versus nurture and the limits of artificial intelligence.Offering a powerful and elegant model that encompasses life’s complexity, Probably Approximately Correct has profound implications for how we think about behavior, cognition, biological evolution, and the possibilities and limits of human and machine intelligence.

    Somehow, within each of our brains, billions of neurons work to create our conscious experience. How does this happen? Why do we experience life in the first person? After over twenty years researching the brain, world-renowned neuroscientist Anil Seth puts forward a radical new theory of consciousness and self. His unique theory of what it means to 'be you' challenges our understanding of perception and reality and it turns what you thought you knew about yourself on its head.'Awe-inspiring and humane.' NEW STATESMAN (Books of the Year)'Fascinating.' FINANCIAL TIMES (Books of the Year)'Profound.' GUARDIAN (Books of the Year)'Brilliant.' CLAIRE TOMALIN, NEW YORK TIMES'Outstanding.' PSYCHOLOGY TODAY 'Amazing . . . a brilliant read.'RUSSELL BRAND'Beautifully written, crystal clear, deeply insightful.'DAVID EAGLEMAN, Pulitzer Prize-nominated author of Livewired'Offers us new cause for astonishment and wonder.'ANNAKA HARRIS, author of Conscious'A fascinating book. A joy to read.'NIGEL WARBURTON'Truly compelling.'PROFESSOR KARL FRISTON, Universty College London'A wonderfully accessible and comprehensive account.'SEAN CARROLL, author of Something Deeply Hidden

    Whether you’re deciding which smart phone to purchase or which politician to believe, you think you are a rational being whose every decision is based on cool, detached logic, but here’s the truth: You are not so smart. You’re just as deluded as the rest of us--but that’s okay, because being deluded is part of being human. Growing out of David McRaney’s popular blog, You Are Not So Smart reveals that every decision we make, every thought we contemplate, and every emotion we feel comes with a story we tell ourselves to explain them, but often these stories aren’t true. Each short chapter--covering topics such as Learned Helplessness, Selling Out, and the Illusion of Transparency--is like a psychology course with all the boring parts taken out.Bringing together popular science and psychology with humor and wit, You Are Not So Smart is a celebration of our irrational, thoroughly human behavior.

    The first six chapters, originally published in the 1960s, made a groundbreaking contribution to linguistic theory. This edition complements them with an additional chapter and a new preface, bringing Chomsky's influential approach into the twenty-first century. Chapters 1-6 present Chomsky's early work on the nature and acquisition of language as a genetically endowed, biological system (Universal Grammar), through the rules and principles of which we acquire an internalized knowledge (I-language). Over the past fifty years, this framework has sparked an explosion of inquiry into a wide range of languages, and has yielded some major theoretical questions. The final chapter revisits the key issues, reviewing the 'biolinguistic' approach that has guided Chomsky's work from its origins to the present day, and raising some novel and exciting challenges for the study of language and mind.

    Gardner's trailblazing book revolutionized the worlds of education and psychology by positing that rather than a single type of intelligence, we have several--most of which are neglected by standard testing and educational methods.More than 200,00 copies of earlier editions have been sold; this reissue includes a new introduction by the author to mark the twenty-first birthday of this remarkable book.Download PDFhttp://uploading.com/files/ae6de5f6/0...http://www.filesonic.com/file/1882814...http://depositfiles.com/files/vx6nj38a9

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    Contemporary research in the empirical neurosciences and recent research in the philosophy of mind and the philosophy of science are used to illuminate fundamental questions concerning the relation between abstract cognitive theory and substantive neuroscience.

    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

    The Archaeology of Mind presents an affective neuroscience approach which takes into consideration basic mental processes, brain functions, and emotional behaviors that all mammals share to locate the neural mechanisms of emotional expression. It reveals for the first time the deep neural sources of our values and basic emotional feelings.This book elaborates on the seven emotional systems that explain how we live and behave. These systems originate in deep areas of the brain that are remarkably similar across all mammalian species. When they are disrupted, we find the origins of emotional disorders:- SEEKING: how the brain generates a euphoric and expectant response- FEAR: how the brain responds to the threat of physical danger and death- RAGE: sources of irritation and fury in the brain- LUST: how sexual desire and attachments are elaborated in the brain- CARE: sources of maternal nurturance- GRIEF: sources of non-sexual attachments- PLAY: how the brain generates joyous, rough-and-tumble interactions- SELF: a hypothesis explaining how affects might be elaborated in the brainThe book offers an evidence-based evolutionary taxonomy of emotions and affects and, as such, a brand-new clinical paradigm for treating psychiatric disorders in clinical practice.

    Why is this? Why, despite the rise of science, technology, and secular education, are people turning to religion in greater numbers than ever before? Why do people believe in God at all?These provocative questions lie at the heart of How We Believe , an illuminating study of God, faith, and religion. Bestselling author Michael Shermer offers fresh and often startling insights into age-old questions, including how and why humans put their faith in a higher power, even in the face of scientific skepticism. Shermer has updated the book to explore the latest research and theories of psychiatrists, neuroscientists, epidemiologists, and philosophers, as well as the role of faith in our increasingly diverse modern world.Whether believers or nonbelievers, we are all driven by the need to understand the universe and our place in it. How We Believe is a brilliant scientific tour of this ancient and mysterious desire.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    Lilly, M.D.This book examines the sacred realms of self, religion, sex, science, philosophy, drugs, politics, money, crime, war, family & spiritual paths "with no holds barred, with courage & a sense of excitement." It provides readers with unique views of their own inner realities to help unfold new areas for growth & self-realization.

    But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.