MARC details
| 000 -LEADER |
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| fixed length control field |
01987nam a22003137a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20241112124732.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
241112b |||||||| |||| 00| 0 hin d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783030623401 |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
NISER LIBRARY |
| Language of cataloging |
eng |
| Transcribing agency |
NISER LIBRARY |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
004.8 |
| Item number |
PHI-M |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Phillips, Jeff M. |
| 245 ## - TITLE STATEMENT |
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| Title |
Mathematical foundations for data analysis |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc. |
Switzerland : |
| Name of publisher, distributor, etc. |
Springer, |
| Date of publication, distribution, etc. |
2021 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvii, 287p. |
| 490 ## - SERIES STATEMENT |
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| Series statement |
Springer Series in the Data Sciences |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation for students planning to take rigorous Machine Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and principal component analysis. It also surveys basic techniques in supervised (regression and classification) and unsupervised learning (dimensionality reduction and clustering) through an accessible, simplified presentation. Students are recommended to have some background in calculus, probability, and linear algebra. Some familiarity with programming and algorithms is useful to understand advanced topics on computational techniques. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Data mining |
| General subdivision |
Mathematics |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine learning |
| General subdivision |
Mathematics |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Data analysis |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Neural networks |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Data sciences |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Dimensionality reduction |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Big data |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
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| Materials specified |
Table of contents |
| Uniform Resource Identifier |
<a href="https://link.springer.com/content/pdf/bfm:978-3-030-62341-8/1">https://link.springer.com/content/pdf/bfm:978-3-030-62341-8/1</a> |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Reviews |
| Uniform Resource Identifier |
<a href="https://www.goodreads.com/book/show/57190260-mathematical-foundations-for-data-analysis?ref=nav_sb_ss_1_13#CommunityReviews">https://www.goodreads.com/book/show/57190260-mathematical-foundations-for-data-analysis?ref=nav_sb_ss_1_13#CommunityReviews</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Universal Decimal Classification |
| Koha item type |
Book |
