MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03459cam a2200433 i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
23532456 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20250904105611.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
240123s2024 flua b 001 0 eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2023036913 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9780367755386 |
| Qualifying information |
(hbk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9780367751968 |
| Qualifying information |
(pbk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| Canceled/invalid ISBN |
9781003162872 |
| Qualifying information |
(ebk.) |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
23532456 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
DLC |
| Modifying agency |
DLC |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
pcc |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA 76.9 |
| Item number |
T78 2024 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Truong, Dothang, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Data science and machine learning for non-programmers : |
| Remainder of title |
using SAS Enterprise miner / |
| Statement of responsibility, etc. |
Dothang Truong. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
First edition. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Boca Raton : |
| Name of producer, publisher, distributor, manufacturer |
CRC Press/Taylor & Francis Group, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2024. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xii, 577 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
27 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 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references (pages 555-559) and index. |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Part I: Introduction to Data Mining. 1. Introduction to Data Mining and Data Science. 2. Data Mining Processes, Methods, and Software. 3. Data Sampling and Partitioning. 4. Data Visualization and Exploration. 5. Data Modification. Part II: Data Mining Methods. 6. Model Evaluation. 7. Regression Methods. 8. Decision Trees. 9. Neural Networks. 10. Ensemble Modeling. 11. Presenting Results and Writing Data Mining Reports. 12. Principal Component Analysis. 13. Cluster Analysis. Part III: Advanced Data Mining Methods. 14. Random Forest. 15. Gradient Boosting. 16. Bayesian Networks. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
"As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this disparity and cater to learners from various non-technical fields, enabling them to utilise machine learning effectively. Adopting a hands-on approach, readers are guided through practical implementations using real datasets and SAS Enterprise Miner, a user-friendly data mining software that requires no programming. Throughout the chapters, two large datasets are used consistently, allowing readers to practice all stages of the data mining process within a cohesive project framework. This book also provides specific guidelines and examples on presenting data mining results and reports, enhancing effective communication with stakeholders. Designed as a guiding companion for both beginners and experienced practitioners, this book targets a wide audience, including students, lecturers, researchers and industry professionals from various backgrounds"-- |
| Assigning source |
Provided by publisher. |
| 590 ## - CITATION |
|---|
| Citation |
Truong, D. (2024). Data science and machine learning for non-programmers: Using SAS Enterprise miner (1st ed.). CRC Press/Taylor & Francis Group. |
| 630 00 - SUBJECT ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Enterprise miner |
| Form subdivision |
Textbooks. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining |
| General subdivision |
Computer programs |
| Form subdivision |
Textbooks. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining |
| General subdivision |
Statistical methods |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning |
| General subdivision |
Study and teaching |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
SAS (Computer program language) |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
7 |
| b |
cbc |
| c |
orignew |
| d |
1 |
| e |
ecip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Book |
| Suppress in OPAC |
No |