Data Science Concepts and Techniques with Applications [2nd ed.] / (Record no. 7199)

MARC details
000 -LEADER
fixed length control field 02039nam a2200229 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251017161238.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 241213b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031174414
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Item number QamD2
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Qamar, Usman
245 ## - TITLE STATEMENT
Title Data Science Concepts and Techniques with Applications [2nd ed.] /
Statement of responsibility, etc Usman Qamar and Muhammad Summair Raza
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Switzerland :
Name of publisher Springer,
Year of publication ©2020.
300 ## - PHYSICAL DESCRIPTION
Number of Pages xxiv, 474p.
520 ## - SUMMARY, ETC.
Summary, etc This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines.<br/><br/>The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared to the first edition, is devoted to various techniques and tools applied in data science. Its chapters 4 to 10 detail data pre-processing, classification, clustering, text mining, deep learning, frequent pattern mining, and regression analysis. Eventually, the third part (chapters 11 and 12) present a brief introduction to Python and R, the two main data science programming languages, and shows in a completely new chapter practical data science in the WEKA (Waikato Environment for Knowledge Analysis), an open-source tool for performing different machine learning and data mining tasks. An appendix explaining the basic mathematical concepts of data science completes the book.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Machine learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Python (computer program language)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Big Data
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Raza, Muhammad Summair
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
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 Copy 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 30/07/2025 Today and Tomorrows Printers and Publishers 4938.00 TTPP/130/2025-26 006.312 QamD2 (11475) 11475 Copy 1 7054.29 30/07/2025 Books