This unique volume is an introduction for computer scientists, including a formal study of theoretical algorithms for Big Data applications, which allows them to work on such algorithms in the future. It also serves as a useful reference guide for the general computer science population, providing a comprehensive overview of the fascinating world of such algorithms. To achieve these goals, the algorithmic results presented have been carefully chosen so that they demonstrate the important techniques and tools used in Big Data algorithms, and yet do not require tedious calculations or a very deep mathematical background

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Annotation

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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 favourites 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 problems for decades. And the solutions they’ve found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian (who holds degrees in computer science, philosophy, and poetry, and works at the intersection of all three) and Tom Griffiths (a UC Berkeley professor of cognitive science and psychology) show how the simple, precise 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 human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

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This title provides a series of brilliantly simple diagrams (‘blueprints’ if you want to be complicated about it) that show how important things work: from the nuclear bomb to the biro. It’s good to know what the parts of a thing are called, but it’s much more interesting to know what they do.

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We depend on–we believe in–algorithms to help us get a ride, choose which book to buy, execute a mathematical proof. It’s as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Humans have always believed that certain invocations–the marriage vow, the shaman’s curse–do not merely describe the world but make it. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking. In What Algorithms Want, Ed Finn considers how the algorithm–in practical terms, a method for solving a problem

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The science is settled on this.

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