Foundations of Data Science / (Record no. 6633)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01707 a2200205 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20251009170327.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 251009b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781108485067 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 004 |
| Item number | BluF |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Blum, Avrim |
| 245 ## - TITLE STATEMENT | |
| Title | Foundations of Data Science / |
| Statement of responsibility, etc | Avrim Blum, John Hopcroft & Ravindran Kannan |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher | Cambridge University Press : |
| Place of publication | New York , |
| Year of publication | ©2020. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | viii,424p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Machine Learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Data Science |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Kannan, Ravindran |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Hopcroft, John |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Collection code | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Purchase Price | Bill number | Full call number | Accession Number | Print Price | Bill Date/Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Computer Science | Indian Institute of Technology Tirupati | Indian Institute of Technology Tirupati | General Stacks | 07/10/2025 | Shah Book House | 3705.46 | SBH/28599 | 004 BluF (12173) | 12173 | 5293.52 | 07/10/2025 | Books |