Hardcover. Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent.Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers:Data-driven modellingPredictive analyticsData analytics and visualization toolsAI-aided applicationsCybersecurity techniquesCloud computingIoT-enabled systems for developing smart financial systemsThis book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices. This book focuses on the opportunities and challenges for data-driven modelling and predictive analytics for business systems. It covers fundamental concepts as well as advanced techniques, technologies, and tools. It discusses technology in the context of innovation, business development, and business management. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Detalles bibliogr�ficos

T�tulo: Data-Driven Modelling and Predictive Analytics in Business and Finance (Hardcover)
Editor: Taylor & Francis Ltd, London
Fecha de publicaci�n: 2024
Idioma: Ingl�s
ISBN 10: 1032601914
ISBN 13: 9781032601915
Encuadernaci�n: Hardcover
Estado: new

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Sinopsis

Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent.

Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers:

Data-driven modelling
Predictive analytics
Data analytics and visualization tools
AI-aided applications
Cybersecurity techniques
Cloud computing
IoT-enabled systems for developing smart financial systems

This book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices.

Acerca del autor

Alex Khang is a Professor of Information Technology, D.Sc. D.Litt., and a AI and Data scientist, AI and Data Science Research Center, Global Research Institute of Technology and Engineering, North Carolina, United States.

Rashmi Gujrati is a Professor, Campus Director, and Dean of International Affairs at Kamal Gandhi Memorial Ayurvedic College, Nawanshahr, India.

Hayri Uygun holds a Ph.D. from Recep Tayyip Erdogan University, Institute of Social Sciences, Business Administration, Rize, Turkey.

R. K. Tailor is an expert in robotic process automation and robotic accounting and a Senior Associate Professor at the Department of Business Administration, Manipal University, Manipal, India.

Sanjaya Singh Gaur is a Clinical Professor of Marketing at the NYU School of Professional Studies in New York University, New York, United States.

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