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Mining of Massive Datasets

Autor Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman
en Limba Engleză Hardback – 13 noi 2014
Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond. This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction.
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Specificații

ISBN-13: 9781107077232
ISBN-10: 1107077230
Pagini: 476
Ilustrații: 150 b/w illus. 210 exercises
Dimensiuni: 180 x 253 x 30 mm
Greutate: 1.07 kg
Ediția:Revizuită
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:New York, United States

Headline


Cuprins

1. Data mining; 2. MapReduce and the new software stack; 3. Finding similar items; 4. Mining data streams; 5. Link analysis; 6. Frequent itemsets; 7. Clustering; 8. Advertising on the web; 9. Recommendation systems; 10. Mining social-network graphs; 11. Dimensionality reduction; 12. Large-scale machine learning; 13. Neural nets and deep learning; Index.

Notă biografică