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Mining of Massive Datasets par Jure Leskovec (anglais) livre relié
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Lieu : Fairfield, Ohio, États-Unis
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Numéro de l'objet eBay :388608610329
Dernière mise à jour : juin 26, 2025 01:20:22 HAEAfficher toutes les modificationsAfficher toutes les modifications
Caractéristiques de l'objet
- État
- ISBN-13
- 9781108476348
- Book Title
- Mining of Massive Datasets
- ISBN
- 9781108476348
À propos de ce produit
Product Identifiers
Publisher
Cambridge University Press
ISBN-10
1108476341
ISBN-13
9781108476348
eBay Product ID (ePID)
12038707628
Product Key Features
Number of Pages
565 Pages
Language
English
Publication Name
Mining of Massive Data Sets
Publication Year
2020
Subject
Databases / Data Mining, Computer Vision & Pattern Recognition
Features
Revised
Type
Textbook
Subject Area
Computers
Format
Hardcover
Dimensions
Item Height
1.1 in
Item Weight
43.7 Oz
Item Length
10 in
Item Width
7 in
Additional Product Features
Edition Number
3
Intended Audience
College Audience
LCCN
2020-012035
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.312
Edition Description
Revised edition
Table Of Content
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.
Synopsis
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 third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs., 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.
LC Classification Number
HF5415.125.L46 2020
Description de l'objet du vendeur
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- w***i (874)- Évaluation laissée par l'acheteur.Dernier moisAchat vérifiéAbsolutely Wonderful Seller!! Terrific Item As Described!!! Great Service and Communication!! Shipped In Waterproof Packaging!! I Received Item In About One Week!! Very Pleased With Seller! I Will Buy From This Seller Again!!
- e***_ (17)- Évaluation laissée par l'acheteur.Six derniers moisAchat vérifiéSeller handles a massive inventory so I give them grace on the slow processing and shipping. They were very communicative and prompt with their response when I messaged in asking about it. Book was in good condition as described. Small ding on the page edges which wasn't mentioned, but that's fairly common even at your typical book store. Still a good value and I'd buy from them again.
- 0***i (5)- Évaluation laissée par l'acheteur.Six derniers moisAchat vérifiéThe first item arrived with some damage to the inside back cover, but the seller responded immediately, assuring me they’d provide a replacement, and even told me I could keep the original. They were upfront about a short delay, and gave a clear estimated ship date, and followed up right on time once it shipped. The replacement arrived in perfect condition and exactly as described. I really appreciated their transparency and professionalism. Would definitely buy from them again!