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Once we look at machine learning this way, two things immediately jump out. The first is that the more data we have, the more we can learn. No data? Nothing to learn. Big data? Lots to learn. That’s why machine learning has been turning up everywhere, driven by exponentially growing mountains of data. If machine …

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The second goal of this book is thus to enableyou to invent the Master Algorithm. You’d think this would require heavy-duty mathematics and severe theoretical work. On the contrary, what it requires is stepping back from the mathematical arcana to see the overarching pattern of learning phenomena; and for this the layman, approaching the forest …

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The argument from neuroscience. Another line of evidence comes from optimization, the branch of mathematics concerned with finding the input to a function that produces its highest output. For example, finding the sequence of stock purchases and sales that maximizes your total returns is an optimization problem. In optimization, simple functions often give rise to …

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Migration transparencymeans that resources must be free to move from one location to another without having their names change. In the example of Fig. 1-10 we saw how server directories could be mounted in arbitrary places in the clients’ directory hierarchy. Since a path like/work/news does not reveal the location of the server, it is location …

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In the preceding sections we have looked at distributed systems and related topics from both the hardware and software points of view. In the remainder of this chapter we will briefly look at some of the key design issues that people contemplating building a distributed operating system must deal with. We will come back to …

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Conjunctive concepts don’t get you very far, though. The problem is that, as Rudyard Kipling said, “There are nine and sixty ways of constructing tribal lays, and every one of them is right.” Real concepts are disjunctive. Chairs can have four legs or one, and sometimes none. You can win at chess in countless different …

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By taking automation to new heights, the machine-learning revolution will cause extensive economic and social changes, just as the Internet, the personal computer, the automobile, and the steam engine did in their time. One area where these changes are already apparent is business.. NP-completeness aside, the sheer existence of computers is itself a powerful sign …

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