Mathematical Problems in Data Science : (Record no. 200433876)

MARC details
000 -LEADER
fixed length control field 04280nam a22004455i 4500
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20231104114233.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151215s2015 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783319251271
Canceled/invalid ISBN 978-3-319-25127-1
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-319-25127-1
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA75.5-76.95
072 #7 - SUBJECT CATEGORY CODE
Subject category code UT
Source bicssc
Subject category code COM069000
Source bisacsh
Subject category code UT
Source thema005.7
-- 23
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title İngilizce
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Chen, Li M.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Mathematical Problems in Data Science :
Remainder of title Theoretical and Practical Methods /
Statement of responsibility, etc. by Li M. Chen, Zhixun Su, Bo Jiang.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cham :
Name of producer, publisher, distributor, manufacturer Springer International Publishing :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2015.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction: Data Science and BigData Computing -- Overview of Basic Methods for Data Science -- Relationship and Connectivity of Incomplete Data Collection -- Machine Learning for Data Science: Mathematical or Computational -- Images, Videos, and BigData -- Topological Data Analysis -- Monte Carlo Methods and their Applications in Big Data Analysis -- Feature Extraction via Vector Bundle Learning -- Curve Interpolation and Financial Curve Construction -- Advanced Methods in Variational Learning: Segmentation with Intensity Inhomogeneity -- An On-line Strategy of Groups Evacuation From a Convex Region in the Plane -- A New Computational Model of Bigdata.
520 ## - SUMMARY, ETC.
Summary, etc. This book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix, Google Page Rank, efficient algorithms, hardness of problems, different types of big data, geometric data structures, topological data processing, and various learning methods. For unsolved problems such as incomplete data relation and reconstruction, the book includes possible solutions and both statistical and computational methods for data analysis. Initial chapters focus on exploring the properties of incomplete data sets and partial-connectedness among data points or data sets. Discussions also cover the completion problem of Netflix matrix; machine learning method on massive data sets; image segmentation and video search. This book introduces software tools for data science and Big Data such MapReduce, Hadoop, and Spark. This book contains three parts. The first part explores the fundamental tools of data science. It includes basic graph theoretical methods, statistical and AI methods for massive data sets. In second part, chapters focus on the procedural treatment of data science problems including machine learning methods, mathematical image and video processing, topological data analysis, and statistical methods. The final section provides case studies on special topics in variational learning, manifold learning, business and financial data rec overy, geometric search, and computing models. Mathematical Problems in Data Science is a valuable resource for researchers and professionals working in data science, information systems and networks. Advanced-level students studying computer science, electrical engineering and mathematics will also find the content helpful.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Information systems.
Topical term or geographic name entry element Computer Communication Networks.
Topical term or geographic name entry element Computer science.
Topical term or geographic name entry element Information Systems and Communication Service.
Authority record control number or standard number http://scigraph.springernature.com/things/product-market-codes/I18008
Topical term or geographic name entry element Computer Communication Networks.
Authority record control number or standard number http://scigraph.springernature.com/things/product-market-codes/I13022
Topical term or geographic name entry element Mathematics of Computing.
Authority record control number or standard number http://scigraph.springernature.com/things/product-market-codes/I17001
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Su, Zhixun.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
Personal name Jiang, Bo.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-319-25127-1">https://doi.org/10.1007/978-3-319-25127-1</a>
Materials specified Springer eBooks
Public note Online access link to the resource
912 ## -
-- ZDB-2-SCS
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type E-Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Not for loan Collection code Home library Current library Date acquired Source of acquisition Coded location qualifier Inventory number Total Checkouts Full call number Barcode Date last seen Date shelved Koha item type Public note
    Library of Congress Classification Geçerli değil-e-Kitap / Not applicable-e-Book E-Kitap Koleksiyonu Merkez Kütüphane Merkez Kütüphane 03/12/2018 Satın Alma / Purchase BİL/YAP   QA75.5-76.95EBK EBK00647 03/12/2018 03/12/2018 E-Book
Devinim Yazılım Eğitim Danışmanlık tarafından Koha'nın orjinal sürümü uyarlanarak geliştirilip kurulmuştur.