MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03219nam a22003137a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20230710105106.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
211112b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9789386279804 |
| 028 ## - DISTRIBUTOR NAME |
|---|
| Distributor Name |
:Variety Books Publishers & Distributors |
| Distributor address |
:B-10 Street No 2 West Vinod Nagar Delhi 110092 |
| Bill Number |
:IM2892 |
| Bill Date |
:02/11/2021 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
004 BLU |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Blum, Avrim |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Foundations of Data Science |
| Statement of responsibility, etc |
/ Avrim Blum |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
New Delhi |
| Name of publisher, distributor, etc |
:Hindustan Book Agency |
| Date of publication, distribution, etc |
2020 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xi,504p. |
| Dimensions |
24cm. |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
820 |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
Taxts and Reading in Mathematics |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Contents note |
"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"-- |
| 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 or geographic name as entry element |
Computer Science |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Data processing and computer science |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Statistics. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Quantitative research. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Big Data |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Data Science |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Blum, Avrim, |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Hopcroft, John E. |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Kannan, Ravindran, |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Mathematics Departmental Library |
