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Datadriven Modelling And Predictive Analytics In Business And Finance Concepts Designs Technologies And Applications Alex Khang

  • SKU: BELL-57257202
Datadriven Modelling And Predictive Analytics In Business And Finance Concepts Designs Technologies And Applications Alex Khang
$ 31.00 $ 45.00 (-31%)

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Datadriven Modelling And Predictive Analytics In Business And Finance Concepts Designs Technologies And Applications Alex Khang instant download after payment.

Publisher: CRC Press
File Extension: PDF
File size: 54.55 MB
Pages: 442
Author: Alex Khang, Rashmi Gujrati, Hayri Uygun, R. K. Tailor & Sanjaya Singh Gaur
Language: English
Year: 2025

Product desciption

Datadriven Modelling And Predictive Analytics In Business And Finance Concepts Designs Technologies And Applications Alex Khang by Alex Khang, Rashmi Gujrati, Hayri Uygun, R. K. Tailor & Sanjaya Singh Gaur instant download after payment.

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.

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