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- EPUB大小:2MBA fascinating exploration of how insights from computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.A fascinating exploration of how insights from computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.0 192浏览会员免费
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- News and articles on arti cial intelligence seem to be everywhere. At least they do if you are writing a book with the words ‘arti cial intelligence’ in the title. But what is arti cial intelligence? Critical as this eld is, it appears that there is no clear de nition. A reporter went to Alphabet (formerly Google), the epicentre of arti cial intel- ligence, and asked people working there for an explanation. Here are some of the answers: ‘I would de nitely interview someone else.’ ‘No thanks. Sorry. Good luck.’ ‘I don’t know. I’ll pass.’ ‘It’s machine learning.’ ‘I work at Yahoo...’ Still, this topic is vitally important for you and for answering the increas- ingly dif cult questions you are likely to encounter. This book will give you the practical information and pointers on applications that you need to know to succeed. But this is vital for your future campaigns, and this book will tell you what you need to know to get ahead. In Chapter 1, we propose a working de nition. There is no question that arti cial intelligence and machine learning, if not in fact the same, overlap substantially. This of course raises the question of what machine learning means. This de nition also varies depending on who you ask, just like asking about the height of PT Barnum’s elephant, Jumbo. (Jumbo was twelve foot six inches high if you asked Mr Barnum, and ten foot nine if you asked someone with a tape measure.) An online article purporting to teach about machine learning included regression and clustering among advanced machine learning methods. These are two of the most august and long-standing of analytical approaches. Regression was widely used well before computers existed. Even taking a less expansive de nition, machine learning has been with us for decades. It has been working in the background as often as in the foreground, solving problems that would have been impossible to approach without it. This is worth noting separately.0 107浏览会员免费
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