MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02626nam a22002657a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
250102s2024 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9780367755386 |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
|---|
| ISSN-L |
9780367755386 |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
English |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.312 |
| Item number |
TRU |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Truong, Dothang |
| 9 (RLIN) |
883690 |
| Relator term |
author |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Data Science and Machine Learning for Non Programmers Using SAS Enterprise Miner |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Boca Raton, FL : |
| Name of publisher, distributor, etc. |
CRC Press, |
| Date of publication, distribution, etc. |
c2024 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xii, 577 p. |
| Other physical details |
: ill |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
Chapman and Hall/CRC Data Mining and Knowledge Discovery Series |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Biography<br/><br/>Dothang Truong, PhD, is a Professor of Graduate Studies at Embry Riddle Aeronautical University, Daytona Beach, Florida. He has extensive teaching and research experience in machine learning, data analytics, air transportation management, and supply chain management. In 2022, Dr. Truong received the Frank Sorenson Award for outstanding achievement of excellence in aviation research and scholarship. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes Bibliographical References and Index |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Summary:<br/>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 utilize machine learning effectively.<br/><br/>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.<br/><br/>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. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
883875 |
| Topical term or geographic name entry element |
Enterprise Miner |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
883874 |
| Topical term or geographic name entry element |
Data Mining Computer Programs |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Link text |
ToC |
| Uniform Resource Identifier |
<a href="https://eaklibrary.neduet.edu.pk:8443/catalog/bk/books/toc/9780367755386.pdf">https://eaklibrary.neduet.edu.pk:8443/catalog/bk/books/toc/9780367755386.pdf</a> |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Link text |
Web Link |
| Uniform Resource Identifier |
<a href="https://www.routledge.com/Data-Science-and-Machine-Learning-for-Non-Programmers-Using-SAS-Enterprise-Miner/Truong/p/book/9780367755386?srsltid=AfmBOoqwGA4KKBDoOqeL2QTsrY7w9Sx5wuf9EhxFZfr9W-ITcEeuiJX7">https://www.routledge.com/Data-Science-and-Machine-Learning-for-Non-Programmers-Using-SAS-Enterprise-Miner/Truong/p/book/9780367755386?srsltid=AfmBOoqwGA4KKBDoOqeL2QTsrY7w9Sx5wuf9EhxFZfr9W-ITcEeuiJX7</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |
