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:
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
EUR 17,64 per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiGRATIS per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiDa: Basi6 International, Irving, TX, U.S.A.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Codice articolo ABEJUNE24-390464
Quantità: 1 disponibili
Da: Speedyhen, London, Regno Unito
Condizione: NEW. Codice articolo NW9781032600628
Quantità: 3 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 47338134-n
Quantità: Più di 20 disponibili
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days. 820. Codice articolo B9781032600628
Quantità: 1 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9781032600628_new
Quantità: Più di 20 disponibili
Da: moluna, Greven, Germania
Condizione: New. 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 Profes. Codice articolo 1280895738
Quantità: 3 disponibili
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Condizione: New. 2016. paperback. . . . . . Codice articolo V9781032600628
Quantità: 3 disponibili
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. pp. 442. Codice articolo 398242645
Quantità: 3 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 47338134
Quantità: Più di 20 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: As New. Unread book in perfect condition. Codice articolo 47338134
Quantità: Più di 20 disponibili