Aref yelghi (31 résultats)
Computing Intelligence in Capital Market
Yelghi, Asef (EDT); Yelghi, Aref (EDT); Apan, Mehmet (EDT); Tavangari, Shirmohammad (EDT)
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Computing Intelligence in Capital Market
Yelghi, Asef (EDT); Yelghi, Aref (EDT); Apan, Mehmet (EDT); Tavangari, Shirmohammad (EDT)
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Computing Intelligence in Capital Market
Yelghi, Asef (EDT); Yelghi, Aref (EDT); Apan, Mehmet (EDT); Tavangari, Shirmohammad (EDT)
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Computing Intelligence in Capital Market
Yelghi, Asef (EDT); Yelghi, Aref (EDT); Apan, Mehmet (EDT); Tavangari, Shirmohammad (EDT)
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Taschenbuch. Etat : Neu. Computing Intelligence in Capital Market | Asef Yelghi (u. a.) | Taschenbuch | v | Englisch | 2025 | Springer | EAN 9783031577109 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Etat : New. pp. 72.
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The book is divided into sections according to the content of the chapters. The first section covers AI concepts with NP and financial issues. The second section covers AI techniques in relation to Fintech issues. The remaining sections are implementat…ion and analysis. As science and technology development and algorithms are widely used in various fields, their influence and development have increased efficiency and productivity. The introduction of algorithms in the financial field has not been an exception to this. In recent years, the growth and development of the financial system have been in sync with the growth of technology. Fintechs were born at the intersection of these two sectors. What happens through the application of computer knowledge in the financial field, or the examination of the efficiency and effectiveness of their use and the interaction and combination of these two fields has been written very infrequently in the majority of books. In Fintech, there are problems that researchers focus on such as customer support, portfolio management, trading algorithms, fraud detection, credit risk assessment, insurance, and wealth management. The mentioned problems are complex and are mapped to NP problems in the field of artificial intelligence. In the last two decades, optimization algorithms, neural networks, and deep learning have been widely applied in many scientific and engineering fields to solve the mentioned problems. The purpose of this book is to provide the reader with the most used artificial intelligence methods for scientific and engineering problems. This book is used by students, scientists, and practitioners in various fields. The chapters are self-explanatory, and the reader can read each one separately. They describe the algorithm used, the chosen problem, and the implementation. In addition, practical examples, comparisons, and experimental results are presented.
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Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The book is divided into sections according to the content of the chapters. The first section covers AI concepts with NP and financial issues. The second section covers AI techniques in relation to Fintech issues. The remaining sections are implementation and… analysis. As science and technology development and algorithms are widely used in various fields, their influence and development have increased efficiency and productivity. The introduction of algorithms in the financial field has not been an exception to this. In recent years, the growth and development of the financial system have been in sync with the growth of technology. Fintechs were born at the intersection of these two sectors. What happens through the application of computer knowledge in the financial field, or the examination of the efficiency and effectiveness of their use and the interaction and combination of these two fields has been written very infrequently in the majority of books. In Fintech, there are problems that researchers focus on such as customer support, portfolio management, trading algorithms, fraud detection, credit risk assessment, insurance, and wealth management. The mentioned problems are complex and are mapped to NP problems in the field of artificial intelligence. In the last two decades, optimization algorithms, neural networks, and deep learning have been widely applied in many scientific and engineering fields to solve the mentioned problems. The purpose of this book is to provide the reader with the most used artificial intelligence methods for scientific and engineering problems. This book is used by students, scientists, and practitioners in various fields. The chapters are self-explanatory, and the reader can read each one separately. They describe the algorithm used, the chosen problem, and the implementation. In addition, practical examples, comparisons, and experimental results are presented.
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Hardcover. Etat : Brand New. 70 pages. 9.25x6.10x9.21 inches. In Stock.
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book unveils the cutting-edge research, ethical insights, and practical applications that are shaping the future of skin health, from faster and more accurate diagnoses to innovative treatment strategies.Artificial Intelligence is transfo…rming dermatology like never before. A must-read for clinicians, researchers, and AI enthusiasts ready to explore the next frontier in dermatology. 128 pp. Englisch.
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
Langue : anglais
Edité par Springer, Berlin|Springer Nature Switzerland|Springer, 2024
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The book is divided into sections according to the content of the chapters. The first section covers AI concepts with NP and financial issues. The second section covers AI techniques in relation to Fintech issue…s. The remaining sections are implementatio.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
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EUR 192,59
EUR 23,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 2 disponible(s)
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book is divided into sections according to the content of the chapters. The first section covers AI concepts with NP and financial issues. The second section covers AI techniques in relation to Fintech issues. The remaining sections… are implementation and analysis. As science and technology development and algorithms are widely used in various fields, their influence and development have increased efficiency and productivity. The introduction of algorithms in the financial field has not been an exception to this. In recent years, the growth and development of the financial system have been in sync with the growth of technology. Fintechs were born at the intersection of these two sectors. What happens through the application of computer knowledge in the financial field, or the examination of the efficiency and effectiveness of their use and the interaction and combination of these two fields has been written very infrequently in the majority of books. In Fintech, there are problems that researchers focus on such as customer support, portfolio management, trading algorithms, fraud detection, credit risk assessment, insurance, and wealth management. The mentioned problems are complex and are mapped to NP problems in the field of artificial intelligence. In the last two decades, optimization algorithms, neural networks, and deep learning have been widely applied in many scientific and engineering fields to solve the mentioned problems. The purpose of this book is to provide the reader with the most used artificial intelligence methods for scientific and engineering problems. This book is used by students, scientists, and practitioners in various fields. The chapters are self-explanatory, and the reader can read each one separately. They describe the algorithm used, the chosen problem, and the implementation. In addition, practical examples, comparisons, and experimental results are presented. 72 pp. Englisch.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 192,59
EUR 23,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 2 disponible(s)
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book is divided into sections according to the content of the chapters. The first section covers AI concepts with NP and financial issues. The second section covers AI techniques in relation to Fintech issues. The remaining sections are im…plementation and analysis. As science and technology development and algorithms are widely used in various fields, their influence and development have increased efficiency and productivity. The introduction of algorithms in the financial field has not been an exception to this. In recent years, the growth and development of the financial system have been in sync with the growth of technology. Fintechs were born at the intersection of these two sectors. What happens through the application of computer knowledge in the financial field, or the examination of the efficiency and effectiveness of their use and the interaction and combination of these two fields has been written very infrequently in the majority of books. In Fintech, there are problems that researchers focus on such as customer support, portfolio management, trading algorithms, fraud detection, credit risk assessment, insurance, and wealth management. The mentioned problems are complex and are mapped to NP problems in the field of artificial intelligence. In the last two decades, optimization algorithms, neural networks, and deep learning have been widely applied in many scientific and engineering fields to solve the mentioned problems. The purpose of this book is to provide the reader with the most used artificial intelligence methods for scientific and engineering problems. This book is used by students, scientists, and practitioners in various fields. The chapters are self-explanatory, and the reader can read each one separately. They describe the algorithm used, the chosen problem, and the implementation. In addition, practical examples, comparisons, and experimental results are presented. 72 pp. Englisch.
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book unveils the cutting-edge research, ethical insights, and practical applications that are shaping the future of skin health, from faster and more accurate diagnoses to innovative treatment strategies. Artificial Intelligence is transformi…ng dermatology like never before. A must-read for clinicians, researchers, and AI enthusiasts ready to explore the next frontier in dermatology.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 136 pp. Englisch.
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Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book unveils the cutting-edge research, ethical insights, and practical applications that are shaping the future of skin health, from faster and more accurate diagnoses to innovative treatment strategies.Artificial Intelligence is transforming… dermatology like never before. A must-read for clinicians, researchers, and AI enthusiasts ready to explore the next frontier in dermatology.
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book is divided into sections according to the content of the chapters. The first section covers AI concepts with NP and financial issues. The second section covers AI techniques in relation to Fintech issues. The remaining sections are… implementation and analysis. As science and technology development and algorithms are widely used in various fields, their influence and development have increased efficiency and productivity. The introduction of algorithms in the financial field has not been an exception to this. In recent years, the growth and development of the financial system have been in sync with the growth of technology. Fintechs were born at the intersection of these two sectors. What happens through the application of computer knowledge in the financial field, or the examination of the efficiency and effectiveness of their use and the interaction and combination of these two fields has been written very infrequently in the majority of books. In Fintech, there are problems that researchers focus on such as customer support, portfolio management, trading algorithms, fraud detection, credit risk assessment, insurance, and wealth management. The mentioned problems are complex and are mapped to NP problems in the field of artificial intelligence. In the last two decades, optimization algorithms, neural networks, and deep learning have been widely applied in many scientific and engineering fields to solve the mentioned problems. The purpose of this book is to provide the reader with the most used artificial intelligence methods for scientific and engineering problems. This book is used by students, scientists, and practitioners in various fields. The chapters are self-explanatory, and the reader can read each one separately. They describe the algorithm used, the chosen problem, and the implementation. In addition, practical examples, comparisons, and experimental results are presented.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 72 pp. Englisch.
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book is divided into sections according to the content of the chapters. The first section covers AI concepts with NP and financial issues. The second section covers AI techniques in relation to Fintech issues. The remaining sections are implem…entation and analysis. As science and technology development and algorithms are widely used in various fields, their influence and development have increased efficiency and productivity. The introduction of algorithms in the financial field has not been an exception to this. In recent years, the growth and development of the financial system have been in sync with the growth of technology. Fintechs were born at the intersection of these two sectors. What happens through the application of computer knowledge in the financial field, or the examination of the efficiency and effectiveness of their use and the interaction and combination of these two fields has been written very infrequently in the majority of books. In Fintech, there are problems that researchers focus on such as customer support, portfolio management, trading algorithms, fraud detection, credit risk assessment, insurance, and wealth management. The mentioned problems are complex and are mapped to NP problems in the field of artificial intelligence. In the last two decades, optimization algorithms, neural networks, and deep learning have been widely applied in many scientific and engineering fields to solve the mentioned problems. The purpose of this book is to provide the reader with the most used artificial intelligence methods for scientific and engineering problems. This book is used by students, scientists, and practitioners in various fields. The chapters are self-explanatory, and the reader can read each one separately. They describe the algorithm used, the chosen problem, and the implementation. In addition, practical examples, comparisons, and experimental results are presented.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 72 pp. Englisch.
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