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Aggiungi al carrelloCondizione: New. CRIS DOLOC is a leading computational scientist with more than 25 years of experience in quantitative finance. He holds a PhD in Computational Physics and is currently teaching at the University of Chicago in the Financial Mathematics program. Cris is also .
Da: GridFreed, North Las Vegas, NV, U.S.A.
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Aggiungi al carrellohardcover. Condizione: New. In shrink wrap. Looks like an interesting title!
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloHardcover. Condizione: Brand New. 272 pages. 9.25x6.25x1.00 inches. In Stock.
Editore: John Wiley & Sons 2019-12-05, 2019
ISBN 10: 1119550505 ISBN 13: 9781119550501
Lingua: Inglese
Da: Chiron Media, Wallingford, Regno Unito
EUR 55,99
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Aggiungi al carrelloHardcover. Condizione: New.
Editore: John Wiley & Sons Inc Dez 2019, 2019
ISBN 10: 1119550505 ISBN 13: 9781119550501
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - 'Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.'- Prof. Terrence J. Sejnowski, Computational NeurobiologistThe main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry.The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic:\* The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence.\* The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance.The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term 'Artificial Intelligence,' especially as it relates to the financial industry.The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author's two decades of professional experience as a technologist, quant and academic.
Da: Kennys Bookstore, Olney, MD, U.S.A.
EUR 83,15
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Aggiungi al carrelloCondizione: New. 2019. Hardcover. . . . . . Books ship from the US and Ireland.
Da: Books Puddle, New York, NY, U.S.A.
EUR 77,44
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Editore: John Wiley & Sons 2019-12-05, 2019
ISBN 10: 1119550505 ISBN 13: 9781119550501
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Da: Chiron Media, Wallingford, Regno Unito
EUR 68,70
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Aggiungi al carrelloHardcover. Condizione: New.
Editore: John Wiley & Sons Inc, New York, 2019
ISBN 10: 1119550505 ISBN 13: 9781119550501
Lingua: Inglese
Da: CitiRetail, Stevenage, Regno Unito
EUR 62,17
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence. Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence.The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term Artificial Intelligence, especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the authors two decades of professional experience as a technologist, quant and academic. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Editore: John Wiley & Sons Inc, New York, 2019
ISBN 10: 1119550505 ISBN 13: 9781119550501
Lingua: Inglese
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 71,19
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence. Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence.The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term Artificial Intelligence, especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the authors two decades of professional experience as a technologist, quant and academic. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
EUR 26,02
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Aggiungi al carrellohardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Editore: John Wiley & Sons Inc, New York, 2019
ISBN 10: 1119550505 ISBN 13: 9781119550501
Lingua: Inglese
Da: Grand Eagle Retail, Fairfield, OH, U.S.A.
EUR 68,69
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence. Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence.The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term Artificial Intelligence, especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the authors two decades of professional experience as a technologist, quant and academic. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.