Learn Data Mining Through Excel : (Record no. 36746)

MARC details
000 -LEADER
fixed length control field 02059cam a22002895i 4500
001 - CONTROL NUMBER
control field 19109225
003 - CONTROL NUMBER IDENTIFIER
control field KCU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240905103725.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160526s2016 nyu 000 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781484259818
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Transcribing agency DLC
Description conventions KCU
Modifying agency AACR2
042 ## - AUTHENTICATION CODE
Authentication code pcc
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Edition number 23
Classification number 006.3
Item number ZHO
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Zhou, Hong
Relator term Author
245 00 - TITLE STATEMENT
Title Learn Data Mining Through Excel :
Remainder of title A Step-by-Step Approach for Understanding Machine Learning Methods /
Statement of responsibility, etc. Hong Zhou
263 ## - PROJECTED PUBLICATION DATE
Projected publication date 1606
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New York, NY :
Name of producer, publisher, distributor, manufacturer Apress,
Date of production, publication, distribution, manufacture, or copyright notice 2020.
300 ## - PHYSICAL DESCRIPTION
Extent xvi, 219 P. ;
Other physical details ill. :
Dimensions 26 cm.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Media type code n
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Carrier type code nc
Source rdacarrier
500 ## - GENERAL NOTE
General note This book teaches you data mining through Excel. You will learn how Excel has an advantage in data mining when the data sets are not too large. It can give you a visual representation of data mining, building confidence in your results. You will go through every step manually, which offers not only an active learning experience, but teaches you how the mining process works and how to find the internal hidden patterns inside the data.
520 ## - SUMMARY, ETC.
Summary, etc. Use popular data mining techniques in Microsoft Excel to better understand machine learning methods.<br/><br/>Software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help.<br/>Excel allows you to work with data in a transparent manner. When you open an Excel file, data is visible immediately and you can work with it directly. Intermediate results can be examined while you are conducting your mining task, offering a deeper understanding of how data is manipulated and results are obtained. These are critical aspects of the model construction process that are hidden in software tools and programming language packages.
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 0
b ibc
c orignew
d 2
e epcn
f 20
g y-gencatlg
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Suppress in OPAC No
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection Home library Current library Shelving location Date acquired Source of acquisition Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type Date last checked out
    Dewey Decimal Classification     Non-fiction KING CEASOR UNIVERSITY LIBRARY KING CEASOR UNIVERSITY LIBRARY Reserve Section 09/05/2024 Purchased   006.3 ZHO 4141 09/05/2024 1 09/05/2024 Books  
    Dewey Decimal Classification     Non-fiction KING CEASOR UNIVERSITY LIBRARY KING CEASOR UNIVERSITY LIBRARY Reserve Section 09/05/2024 Purchased 1 006.3 ZHO 4166 08/04/2025 2 09/05/2024 Books 08/04/2025
© Copyright 2011-2026 - King Ceasor University - All Rights Reserved.
Email: [email protected]