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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Mining of Massive Datasets (Hardcover, 3rd Revised edition)
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Mining of Massive Datasets (Hardcover, 3rd Revised edition)
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Written by leading authorities in database and Web technologies,
this book is essential reading for students and practitioners
alike. The popularity of the Web and Internet commerce provides
many extremely large datasets from which information can be gleaned
by data mining. This book focuses on practical algorithms that have
been used to solve key problems in data mining and can be applied
successfully to even the largest datasets. It begins with a
discussion of the MapReduce framework, an important tool for
parallelizing algorithms automatically. The authors explain the
tricks of locality-sensitive hashing and stream-processing
algorithms for mining data that arrives too fast for exhaustive
processing. Other chapters cover the PageRank idea and related
tricks for organizing the Web, the problems of finding frequent
itemsets, and clustering. This third edition includes new and
extended coverage on decision trees, deep learning, and mining
social-network graphs.
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