Mining of masive datasets Jure Leskovec; Anand Rajaraman; Jeffrey D Ullman
Material type:
TextPublication details: Cambridge : Cambridge University Press , 2020Edition: 3RDDescription: 553 pISBN: - 9781108476348
- 006.312 LES
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IIITDM Kurnool General Stacks | Non-fiction | 006.312 LES (Browse shelf(Opens below)) | Checked out | 29.12.2025 | 0003795 |
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IIITDM Kurnool Reference | Reference | 006.312 LES (Browse shelf(Opens below)) | Not For Loan | 0003796 |
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| 006.3 RUS Artificial intelligence: A modern approach | 006.31 GOO Deep learning | 006.312 DUD Pattern Recognition, | 006.312 LES Mining of masive datasets | 006.312 LIU Sentiment analysis : | 006.312 ROS Fuzzy Sets and Fuzzy Logic with Engineering Applications, , | 006.312 ZAK Data mining and machine learning : |
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
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
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