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

fintech, risk analytics, financial analytics, machine learning, deep learning
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 deploy intelligent solutions, 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.
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 exp