9781119685241 - deep learning in quantitative finance (wiley finance) de green, andrew (30 resultados)
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Hardcover. Condición: new. Hardcover. The complete and practical guide to one of the hottest topics in quantitative finance Deep learning, that is, the use of deep neural networks, is now one of the hottest topics amongst quantitative analysts. Deep Learning in Quantitative Finance provides a comprehensive treatment of deep lear…ning and describes a wide range of applications in mainstream quantitative finance. Inside, youll find over ten chapters which apply deep learning to multiple use cases across quantitative finance. Youll also gain access to a companion site containing a set of Jupyter notebooks, developed by the author, that use Python to illustrate the examples in the text. Readers will be able to work through these examples directly. This book is a complete resource on how deep learning is used in quantitative finance applications. It introduces the basics of neural networks, including feedforward networks, optimization, and training, before proceeding to cover more advanced topics. Youll also learn about the most important software frameworks. The book then proceeds to cover the very latest deep learning research in quantitative finance, including approximating derivative values, volatility models, credit curve mapping, generating realistic market data, and hedging. The book concludes with a look at the potential for quantum deep learning and the broader implications deep learning has for quantitative finance and quantitative analysts. Covers the basics of deep learning and neural networks, including feedforward networks, optimization and training, and regularization techniquesOffers an understanding of more advanced topics like CNNs, RNNs, autoencoders, generative models including GANs and VAEs, and deep reinforcement learningDemonstrates deep learning application in quantitative finance through case studies and hands-on applications via the companion websiteIntroduces the most important software frameworks for applying deep learning within finance This book is perfect for anyone engaged with quantitative finance who wants to get involved in a subject that is clearly going to be hugely influential for the future of finance. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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- Primera edición
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Condición: New. 2026. 1st Edition. hardcover. . . . . .
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Hardcover. Condición: new. Hardcover. The complete and practical guide to one of the hottest topics in quantitative finance Deep learning, that is, the use of deep neural networks, is now one of the hottest topics amongst quantitative analysts. Deep Learning in Quantitative Finance provides a comprehensive treatment of deep lear…ning and describes a wide range of applications in mainstream quantitative finance. Inside, youll find over ten chapters which apply deep learning to multiple use cases across quantitative finance. Youll also gain access to a companion site containing a set of Jupyter notebooks, developed by the author, that use Python to illustrate the examples in the text. Readers will be able to work through these examples directly. This book is a complete resource on how deep learning is used in quantitative finance applications. It introduces the basics of neural networks, including feedforward networks, optimization, and training, before proceeding to cover more advanced topics. Youll also learn about the most important software frameworks. The book then proceeds to cover the very latest deep learning research in quantitative finance, including approximating derivative values, volatility models, credit curve mapping, generating realistic market data, and hedging. The book concludes with a look at the potential for quantum deep learning and the broader implications deep learning has for quantitative finance and quantitative analysts. Covers the basics of deep learning and neural networks, including feedforward networks, optimization and training, and regularization techniquesOffers an understanding of more advanced topics like CNNs, RNNs, autoencoders, generative models including GANs and VAEs, and deep reinforcement learningDemonstrates deep learning application in quantitative finance through case studies and hands-on applications via the companion websiteIntroduces the most important software frameworks for applying deep learning within finance This book is perfect for anyone engaged with quantitative finance who wants to get involved in a subject that is clearly going to be hugely influential for the future of finance. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Librería: moluna, Greven, Alemaniamoluna
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EUR 87,26
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Condición: New. KlappentextThe complete and practical guide to one of the hottest topics in quantitative finance Deep learning, that is, the use of deep neural networks, is now one of the hottest topics amongst quantitative analysts. Deep L.
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Librería: UK BOOKS STORE, London, LONDO, Reino UnidoUK BOOKS STORE
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Hardcover. Condición: New Books. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will b…e requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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- Edición internacional
Librería: UK BOOKS STORE, London, LONDO, Reino UnidoUK BOOKS STORE
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EUR 141,74
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Condición: New Books. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested… if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 400 pages. 9.61x6.69x11.00 inches. In Stock.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 91,94
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Buch. Condición: Neu. Neuware - The complete and practical guide to one of the hottest topics in quantitative finance Deep learning, that is, the use of deep neural networks, is now one of the hottest topics amongst quantitative analysts. Deep Learning in Quantitative Finance provides a comprehensive treatment of deep learning a…nd describes a wide range of applications in mainstream quantitative finance. Inside, you'll find over ten chapters which apply deep learning to multiple use cases across quantitative finance. You'll also gain access to a companion site containing a set of Jupyter not Elektronisches Buch, developed by the author, that use Python to illustrate the examples in the text. Readers will be able to work through these examples directly. This book is a complete resource on how deep learning is used in quantitative finance applications. It introduces the basics of neural networks, including feedforward networks, optimization, and training, before proceeding to cover more advanced topics. You'll also learn about the most important software frameworks. The book then proceeds to cover the very latest deep learning research in quantitative finance, including approximating derivative values, volatility models, credit curve mapping, generating realistic market data, and hedging. The book concludes with a look at the potential for quantum deep learning and the broader implications deep learning has for quantitative finance and quantitative analysts. - Covers the basics of deep learning and neural networks, including feedforward networks, optimization and training, and regularization techniques - Offers an understanding of more advanced topics like CNNs, RNNs, autoencoders, generative models including GANs and VAEs, and deep reinforcement learning - Demonstrates deep learning application in quantitative finance through case studies and hands-on applications via the companion website - Introduces the most important software frameworks for applying deep learning within finance This book is perfect for anyone engaged with quantitative finance who wants to get involved in a subject that is clearly going to be hugely influential for the future of finance.
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Librería: preigu, Osnabrück, Alemaniapreigu
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EUR 97,25
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Buch. Condición: Neu. Deep Learning in Quantitative Finance | Andrew Green | Buch | Wiley Finance | Einband - fest (Hardcover) | Englisch | 2026 | John Wiley & Sons Inc | EAN 9781119685241 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Hardcover. Condición: new. Hardcover. The complete and practical guide to one of the hottest topics in quantitative finance Deep learning, that is, the use of deep neural networks, is now one of the hottest topics amongst quantitative analysts. Deep Learning in Quantitative Finance provides a comprehensive treatment of deep lear…ning and describes a wide range of applications in mainstream quantitative finance. Inside, youll find over ten chapters which apply deep learning to multiple use cases across quantitative finance. Youll also gain access to a companion site containing a set of Jupyter notebooks, developed by the author, that use Python to illustrate the examples in the text. Readers will be able to work through these examples directly. This book is a complete resource on how deep learning is used in quantitative finance applications. It introduces the basics of neural networks, including feedforward networks, optimization, and training, before proceeding to cover more advanced topics. Youll also learn about the most important software frameworks. The book then proceeds to cover the very latest deep learning research in quantitative finance, including approximating derivative values, volatility models, credit curve mapping, generating realistic market data, and hedging. The book concludes with a look at the potential for quantum deep learning and the broader implications deep learning has for quantitative finance and quantitative analysts. Covers the basics of deep learning and neural networks, including feedforward networks, optimization and training, and regularization techniquesOffers an understanding of more advanced topics like CNNs, RNNs, autoencoders, generative models including GANs and VAEs, and deep reinforcement learningDemonstrates deep learning application in quantitative finance through case studies and hands-on applications via the companion websiteIntroduces the most important software frameworks for applying deep learning within finance This book is perfect for anyone engaged with quantitative finance who wants to get involved in a subject that is clearly going to be hugely influential for the future of finance. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.



