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Artificial Intelligence and Machine Learning in Business Management

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4th Industrial Revolution
advanced AI business case studies
Age Group_Uncategorized
Age Group_Uncategorized
Ai Application
Ai Technique
Ai Technology
artificial intelligence
automatic-update
B01=Ahmed A. Elngar
B01=R. Balamurali
B01=Sandeep Kumar Panda
B01=Vaibhav Mishra
Baidu Index
banking business
business management
Category1=Non-Fiction
Category=KJM
COP=United Kingdom
COVID-19
Credit Card Fraud Detection
Dataset
Deep Learning Architecture
Deep Neural Network Model
Delivery_Pre-order
E-learning
employee churn management
eq_bestseller
eq_business-finance-law
eq_isMigrated=2
eq_nobargain
eq_non-fiction
ethical issues
F1 Score
forex prediction
German Data Sets
GRNN
healthcare system
Hidden Layers
human resource analytics
Indian retail companies
investment forecasting
knowledge management systems
Language_English
LSTM
machine learning
marketing automation
marketing strategy
Ml
MLP
Model BPNN
Neural Network
NN
PA=Not yet available
personalized care
predictive analytics
Price_€50 to €100
PS=Forthcoming
Random Forest
risk assessment models
RNN
Roc Curve
semantic data extraction
Sigmoid Activation Function
Smite
softlaunch
supply chain optimization
SVM
SVR
video analysis

Product details

  • ISBN 9780367645564
  • Weight: 440g
  • Dimensions: 156 x 234mm
  • Publication Date: 04 Oct 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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Description

Artificial Intelligence and Machine Learning in Business Management

The focus of this book is to introduce artificial intelligence (AI) and machine learning (ML) technologies into the context of business management. The book gives insights into the implementation and impact of AI and ML to business leaders, managers, technology developers, and implementers.

With the maturing use of AI or ML in the field of business intelligence, this book examines several projects with innovative uses of AI beyond data organization and access. It follows the Predictive Modeling Toolkit for providing new insight on how to use improved AI tools in the field of business. It explores cultural heritage values and risk assessments for mitigation and conservation and discusses on-shore and off-shore technological capabilities with spatial tools for addressing marketing and retail strategies, and insurance and healthcare systems.

Taking a multidisciplinary approach for using AI, this book provides a single comprehensive reference resource for undergraduate, graduate, business professionals, and related disciplines.