Description
Artificial Intelligence and Machine Learning in Business Management
Concepts, Challenges, and Case Studies
Coordinators: Panda Sandeep Kumar, Mishra Vaibhav, Balamurali R., Elngar Ahmed A.
Language: EnglishSubjects for Artificial Intelligence and Machine Learning in Business...:
Keywords
Deep Neural Network Model; Dataset; Roc Curve; Ai Technology; Ai Application; Credit Card Fraud Detection; F1 Score; Model BPNN; Ml; Ai Technique; German Data Sets; SVR; SVM; LSTM; MLP; RNN; Sigmoid Activation Function; NN; Neural Network; Random Forest; Baidu Index; Smite; Hidden Layers; GRNN; Deep Learning Architecture
· 15.6x23.4 cm · Hardback
Description
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Arti?cial 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.
1. Introduction to AI & ML. 2. Impact of AI & ML in Operations Management. 3. Impact of AI & ML in Marketing. 4. Impact of AI & ML in Human Resource Management. 5. Impact of AI & ML in Finance. 6. Impact of AI & ML in Strategy. 7. Impact of AI & ML on Society and Governments. 8. Logistics and Supply Chain Management. 9. Manufacturing and Industrial. 10. Advertisement and Customer Relationship. 11. Knowledge Management, Talent Management. 12. E-Governance and E-Learning.