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Machine learning for managers (Record no. 10309)

MARC details
000 -LEADER
fixed length control field	02368nam a22002177a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field	20251013172929.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field	251009b \|\|\|\|\|\|\|\| \|\|\|\| 00\| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number	9781032362427
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number	006.31
Item number	GEE
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name	Geertsema, Paul
245 ## - TITLE STATEMENT
Title	Machine learning for managers
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc.	New York
Name of publisher, distributor, etc.	Routledge
Date of publication, distribution, etc.	2023
300 ## - PHYSICAL DESCRIPTION
Extent	xx, 159 p.
365 ## - TRADE PRICE
Price type code	INR
Price amount	3963.09
500 ## - GENERAL NOTE
General note	Table of contents:<br/>Part 1: Understanding Machine Learning 1. Let's jump right in 2. Different kinds of ML 3. Creating ML models 4. Linear models 5. Neural networks 6. Tree-based approaches, ensembles and boosting 7. Dimensionality reduction and clustering 8. Unstructured data 9. Explainable AI Part 2: Managing Machine Learning Projects 10. The ML system lifecycle 11. The big picture 12. Creating value with ML 13. Making the business case 14. The ML pipeline 15. Development 16. Deployment and monitoring <br/><br/>[https://www.routledge.com/Machine-Learning-for-Managers/Geertsema/p/book/9781032362427?srsltid=AfmBOooSJRtQzXKcnNVQVw2y4_P_OeCEw23HaLPpDvsyDiyF-cj5a69x]
520 ## - SUMMARY, ETC.
Summary, etc.	Machine learning can help managers make better predictions, automate complex tasks and improve business operations. Managers who are familiar with machine learning are better placed to navigate the increasingly digital world we live in. There is a view that machine learning is a highly technical subject that can only be understood by specialists. However, many of the ideas that underpin machine learning are straightforward and accessible to anyone with a bit of curiosity. This book is for managers who want to understand what machine learning is about, but who lack a technical background in computer science, statistics or math.<br/><br/>The book describes in plain language what machine learning is and how it works. In addition, it explains how to manage machine learning projects within an organization.<br/><br/>This book should appeal to anyone that wants to learn more about using machine learning to drive value in real-world organizations.<br/><br/>(https://www.routledge.com/Machine-Learning-for-Managers/Geertsema/p/book/9781032362427?srsltid=AfmBOooSJRtQzXKcnNVQVw2y4_P_OeCEw23HaLPpDvsyDiyF-cj5a69x)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element	Machine learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element	Industrial managemnent--Technological innovations
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element	Organizational effectiveness
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type	Book
Source of classification or shelving scheme	Dewey Decimal Classification

Holdings
Withdrawn status	Lost status	Source of classification or shelving scheme	Damaged status	Not for loan	Collection code	Bill No	Bill Date	Home library	Current library	Shelving location	Date acquired	Source of acquisition	Cost, normal purchase price	Total Checkouts	Full call number	Accession Number	Date last seen	Copy number	Cost, replacement price	Price effective from	Koha item type
		Dewey Decimal Classification			IT & Decisions Sciences	IN32489	20-09-2025	Indian Institute of Management LRC	Indian Institute of Management LRC	General Stacks	10/05/2025	Overseas Press India Private	2576.01		006.31 GEE	009017	10/05/2025	1	3963.09	10/05/2025	Book