國立虎尾科技大學 |

Machine learning and data sciences for financial markets : = a guide to contemporary practices /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Machine learning and data sciences for financial markets :/ edited by Agostino Capponi, Charles-Albert Lehalle.
Reminder of title:	a guide to contemporary practices /
other author:	Capponi, Agostino,
Description:	1 online resource (xxii, 719 pages) :illustrations (black and white, and colour), digital, PDF files(s) :
Notes:	Also issued in print: 2023.
Subject:	Finance - Data processing. -
Online resource:	https://doi.org/10.1017/9781009028943
ISBN:	9781009028943

Machine learning and data sciences for financial markets : = a guide to contemporary practices /
Machine learning and data sciences for financial markets :a guide to contemporary practices /edited by Agostino Capponi, Charles-Albert Lehalle. - 1 online resource (xxii, 719 pages) :illustrations (black and white, and colour), digital, PDF files(s)

Also issued in print: 2023.

Includes bibliographical references and index.

Leveraging the research efforts of more than sixty experts in the area, this volume reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence.

Specialized.

ISBN: 9781009028943No price

Standard No.: 10.1017/9781009028943doiSubjects--Topical Terms:

559347
Finance
--Data processing.

LC Class. No.: HG104 / .M3 2023

Dewey Class. No.: 332.0285631

Machine learning and data sciences for financial markets : = a guide to contemporary practices /
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520 8 $a Leveraging the research efforts of more than sixty experts in the area, this volume reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence.
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