It all boils down to what Dr. Cate calls the Fatburn Factor, or the body’s natural-born ability to burn body fat as fuel. After years of research and observing the patients in her practice, Dr. Cate discovered that there are certain enzymes required for the body to seek out and utilize body fat for energy. Without these enzymes, people lose the ability to burn fat, making weight gain almost unavoidable. Worse, the loss of your fat-burning enzymes causes your cells to depend on sugar for energy. This leads to elevated blood sugar, putting you at risk for diabetes, and disrupts nearly every hormone in your body. Now, in The Fatburn Fix, Dr. Cate lays out a step-by-step plan to help reboot your fat burn potential in as little as two weeks, opening the door to a lifetime of looking and feeling better than you ever thought possible. This comprehensive guide includes complete meal plans, recipes, and exercise tips that not only repair damage to your metabolism, but also address the number one cause of weight retention and regain. How does it work? The program magnifies your fat burn capacity by training your cells to burn body fat on demand. By making a few changes what you eat (and when)—such as reducing carbohydrates, switching out toxic fats for healthy ones, and adding high-quality proteins—your body will produce the enzymes that allow it to seek out and utilize body fat for energy. Regaining your fat burn potential allows you to free yourself from dependence on sugar – and avoid a constellation of chronic diseases as a result.Improving your Fatburn Factor is the key to a new, healthier relationship between you and your body, paving the way for a faster, smoother, and more permanent journey to optimum health, weight, and happiness.

    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.

    What will the world look like in 2020, 2030 or even 2100? How will progress in scientific research affect human life in the areas of health and lifestyle, energy and the environment, politics and conflict, space exploration and even the ultimate questions of existence? This book offers an electrifying trip through the wonders - and terrors - awaiting us over the next hundred years. The ideas explored include: Therapeutic cloning Regenerative medicine Nanotechnology Quantum computers Cyber-warfare Space colonies The nature of consciousness Digital democracy About the Author: Richard Watson Richard Watson is an internationally renowned author,speaker,futurist and scenario planner who is best known for hisbook FutureFiles and for his graphic representations of futuretrends. Richardis the founder of www.nowandnext.com a website thatpublishes thequarterly Whats Next report, a monthly newsletter anda daily blog.He is a regular on the conference circuit worldwideand recentspeaking clients have included London Business School,Shell andIBM.

     Pioneering book in emerging field from two leading authorities Reviews in an accessible style what we know about how and when the brain learns Draws out the implications of this knowledge for educational policy and practice Covers studies on learning during the whole of development, including adulthood Looks at what we can learn from brain research about children with learning difficulties, and how this can inform remedial education

    Jason Briggs, author of the popular online tutorial "Snake Wrangling for Kids," begins with the basics of how to install Python and write simple commands. In bite-sized chapters, he instructs readers on the essentials of Python, including how to use Python's extensive standard library, the difference between strings and lists, and using for-loops and while-loops. By the end of the book, readers have built a game and created drawings with Python's graphics library, Turtle. Each chapter closes with fun and relevant exercises that challenge the reader to put their newly acquired knowledge to the test.

    From vast deserts to an Indonesian fishing boat, a slow train through Burma to an armed confrontation in Laos, lullabies from middle-aged Chinese businessmen to a cold night on the Great Wall, wolves and reindeer herders, thieves and nomads: this is a vivid illustration of Asia and the people who live there, and of one ancient, stubborn motorcycle travelling through the world's wild places.

    Or, to be precise, it explores how everything is connected from code to culture. We think we're designing software, services, and experiences, but we're not. We are intervening in ecosystems. Until we open our minds, we will forever repeat our mistakes. In this spirited tour of information architecture and systems thinking, Peter Morville connects the dots between authority, Buddhism, classification, synesthesia, quantum entanglement, and volleyball. In 1974 when Ted Nelson wrote "everything is deeply intertwingled," he hoped we might realize the true potential of hypertext and cognition. This book follows naturally from that.

    according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog "AI Weirdness." She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans--all to understand the technology that governs so much of our daily lives.We rely on AI every day for recommendations, for translations, and to put cat ears on our selfie videos. We also trust AI with matters of life and death, on the road and in our hospitals. But how smart is AI really, and how does it solve problems, understand humans, and even drive self-driving cars?Shane delivers the answers to every AI question you've ever asked, and some you definitely haven't--like, how can a computer design the perfect sandwich? What does robot-generated Harry Potter fan-fiction look like? And is the world's best Halloween costume really "Vampire Hog Bride"?In this smart, often hilarious introduction to the most interesting science of our time, Shane shows how these programs learn, fail, and adapt--and how they reflect the best and worst of humanity. You Look Like a Thing and I Love You is the perfect book for anyone curious about what the robots in our lives are thinking.

    He brings new perspectives to age-old conundrums while also tackling modern-day dilemmas -- some for the first time. Begin your warm up by contemplating whether a pickled sheep can truly be considered art, or dive right in and tackle the existence of God. In this radically new way of looking at philosophy, Stephen Law illustrates the problem with a story, then lets the argument battle it out in clear, easily digestible and intelligent prose. This perfect little mental health club is sure to give each reader's mind a great workout.

    Learn how cultivate the extraordinary in your life with a step-by-step guide to transcendent self-change. It is your blueprint to the miraculous.From PEN Award-winning historian and bestselling author Mitch Horowitz (“solid gold”—David Lynch), The Miracle Habits is a natural adjunct to Mitch’s widely acclaimed The Miracle Club, with appeal to spiritual seekers, self-starters, businesspeople, and self-help readers.

    In his latest book, you’ll learn exactly how to rebuild your motivation and sustain it over the long-term.  Master Your Motivation is a clear and concise walkthrough that demonstrates how to regain your motivation. Through Thibaut’s straight-to-the-point instructions, you’ll learn how to build motivation and overcome procrastination. As a result, you will remove guilt and move forward with your life.      In Master Your Motivation, you’ll discover: the one thing you need to do right now to unstick yourself and get your motivation back how to declutter your mind and your environment to let your inner drive come back 25 simple yet powerful strategies to regain your motivation  a simple method to boost your self-esteem and turbocharge your motivation a powerful framework to build momentum and sustain motivation long-term, and much more. Master Your Motivation is your must-read guide for regaining your motivation and living the life you want. If you like easy-to-understand strategies, practical exercises, and no-nonsense teachers, you’ll love this book. Buy Master Your Motivation to get your motivation back today! This book is the second book in the "Mastery Series" below: Book 1 - Master Your Emotions: A Practical Guid to Overcome Negativity and Better Manage Your Feelings Book 2 - Master Your Motivation: A Practical Guide to Unstick Yourself, Build Momentum and Sustain Long-Term Motivation

    T-Minus: The Race to the Moon is the story of the people who made it happen, both in the rockets and behind the scenes.

    When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning—major trends, possible developments, and significant challenges.