Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    He coined the word for it--cybernetics. In God & Golem, Inc., the author concerned himself with major points in cybernetics which are relevant to religious issues.The first point he considers is that of the machine which learns. While learning is a property almost exclusively ascribed to the self-conscious living system, a computer now exists which not only can be programmed to play a game of checkers, but one which can learn from its past experience and improve on its own game. For a time, the machine was able to beat its inventor at checkers. It did win, writes the author, and it did learn to win; and the method of its learning was no different in principle from that of the human being who learns to play checkers.A second point concerns machines which have the capacity to reproduce themselves. It is our commonly held belief that God made man in his own image. The propagation of the race may also be interpreted as a function in which one living being makes another in its own image. But the author demonstrates that man has made machines which are very well able to make other machines in their own image, and these machine images are not merely pictorial representations but operative images. Can we then say: God is to Golem as man is to Machines? in Jewish legend, golem is an embryo Adam, shapeless and not fully created, hence a monster, an automation.The third point considered is that of the relation between man and machine. The concern here is ethical. render unto man the things which are man's and unto the computer the things which are the computer's, warns the author. In this section of the book, Dr. Wiener considers systems involving elements of man and machine. The book is written for the intellectually alert public and does not involve any highly technical knowledge. It is based on lectures given at Yale, at the Soci�t� Philosophique de Royaumont, and elsewhere.

    This 'outside-in' method fueled a generation of brain research and now must confront hidden assumptions about causation and concepts that may not hold neatly for systems that act and react.György Buzsáki's The Brain from Inside Out examines why the outside-in framework for understanding brain function has become stagnant and points to new directions for understanding neural function. Building upon the success of 2011's Rhythms of the Brain, Professor Buzsáki presents the brain as a foretelling device that interacts with its environment through action and the examination of action's consequence. Consider that our brains are initially filled with nonsense patterns, all of which are gibberish until grounded by action-based interactions. By matching these nonsense "words" to the outcomes of action, they acquire meaning. Once its circuits are "calibrated" by action and experience, the brain can disengage from its sensors and actuators, and examine "what happens if" scenarios by peeking into its own computation, a process that we refer to as cognition.The Brain from Inside Out explains why our brain is not an information-absorbing coding device, as it is often portrayed, but a venture-seeking explorer constantly controlling the body to test hypotheses. Our brain does not process information: it creates it.

    A director in theoretical neuroscience introduces readers to the latest findings in the science of decision-making, offering an accessible discussion of the origins of aesthetic choices, ethical behavior, financial decisions, and more, in an account that also connects behavioral science to mental illness and addiction.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Their pioneering work, presented here in an elegant style, challenges much of the conventional wisdom about consciousness. The Universe of Consciousness has enormous implications for our understanding of language, thought, emotion, and mental illness.

    This event—the “intelligence explosion”—will be the most important event in our history, and navigating it wisely will be the most important thing we can ever do.Luminaries from Alan Turing and I. J. Good to Bill Joy and Stephen Hawking have warned us about this. Why do I think Hawking and company are right, and what can we do about it?Facing the Intelligence Explosion is my attempt to answer these questions.

    

    This accessible book introduces you to landmark studies as well as the cutting-edge research that defines this fascinating field. To help you further experiment with and understand the concepts in the text, you can use COGLAB 2.0: THE ONLINE COGNITIVE PSYCHOLOGY LABORATORY. Available at www.academic.cengage.com, COGLAB contains dozens of classic experiments designed to help you learn about cognitive concepts and how the mind works.

    By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.

    Psychiatrist and psychoanalyst, Norman Doidge, M.D., traveled the country to meet both the brilliant scientists championing neuroplasticity and the people whose lives they’ve transformed - people whose mental limitations or brain damage were seen as unalterable. We see a woman born with half a brain that rewired itself to work as a whole, blind people who learn to see, learning disorders cured, IQs raised, aging brains rejuvenated, stroke patients learning to speak, children with cerebral palsy learning to move with more grace, depression and anxiety disorders successfully treated, and lifelong character traits changed. Using these marvelous stories to probe mysteries of the body, emotion, love, sex, culture, and education, Dr. Doidge has written an immensely moving, inspiring book that will permanently alter the way we look at our brains, human nature, and human potential.

    The topic everyone in the world should be talking about.

    Unveiling here the kind of cutting-edge research that has made them giants in their fields, Daniel Goleman and Richard Davidson show us the truth about what meditation can really do for us, as well as exactly how to get the most out of it.Sweeping away common misconceptions and neuromythology to open readers' eyes to the ways data has been distorted to sell mind-training methods, the authors demonstrate that beyond the pleasant states mental exercises can produce, the real payoffs are the lasting personality traits that can result. But short daily doses will not get us to the highest level of lasting positive change--even if we continue for years--without specific additions. More than sheer hours, we need smart practice, including crucial ingredients such as targeted feedback from a master teacher and a more spacious, less attached view of the self, all of which are missing in widespread versions of mind training. The authors also reveal the latest data from Davidson's own lab that point to a new methodology for developing a broader array of mind-training methods with larger implications for how we can derive the greatest benefits from the practice.Exciting, compelling, and grounded in new research, this is one of those rare books that has the power to change us at the deepest level.

    During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.

    Ramachandran, now shares his unique insight into human consciousness in an entertaining, inspiring, and intellectually dazzling brief tour of the ultimate frontier—the thoughts in our heads.A Brief Tour of Human Consciousness is made up of five investigations of the greatest mysteries of the brain. The first chapter shows how amputees feel pain in limbs they no longer have as it introduces the great revolution of our age: neuroscience. The second chapter walks through the way what we see determines our thoughts, and demonstrates the counterintuitive point that believing is in fact seeing. The third chapter takes a leap beyond cutting edge science to audaciously set out a general theory of beauty, explaining why, the world over, cultures have fundamentally similar notions of what is attractive. The fourth chapter explores the bizarre world of synesthetes, people who see colors in numbers, textures in smells, sounds in sights, and flavors in sounds. Finally, V. S. Ramachandran one of the foremost brain researchers in the world today, sums up the implications of the revolution in our understanding of consciousness, to make a fascinating argument about our essential sense of self and its distributed nature.