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Books > Computing & IT > Applications of computing > Signal processing
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Small Summaries for Big Data (Hardcover)
Loot Price: R1,468
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Small Summaries for Big Data (Hardcover)
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The massive volume of data generated in modern applications can
overwhelm our ability to conveniently transmit, store, and index
it. For many scenarios, building a compact summary of a dataset
that is vastly smaller enables flexibility and efficiency in a
range of queries over the data, in exchange for some approximation.
This comprehensive introduction to data summarization, aimed at
practitioners and students, showcases the algorithms, their
behavior, and the mathematical underpinnings of their operation.
The coverage starts with simple sums and approximate counts,
building to more advanced probabilistic structures such as the
Bloom Filter, distinct value summaries, sketches, and quantile
summaries. Summaries are described for specific types of data, such
as geometric data, graphs, and vectors and matrices. The authors
offer detailed descriptions of and pseudocode for key algorithms
that have been incorporated in systems from companies such as
Google, Apple, Microsoft, Netflix and Twitter.
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