Machine Learning and Data Sciences for Financial Markets. A Guide to Contemporary Practices, Hardback

Written by more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets, and explores connections with data science and more traditional approaches. This is an invaluable resource for researchers and graduate students in financial engineering, as well as practitioners in the sector.

• Publisher: Cambridge University Press
• Author(s): Charles-Albert (Abu Dhabi Investment Authority) Lehalle
• Illustration(s): Worked examples or Exercises
• Number of pages: 741
• Publication date: 2023
• Dimensions: 185 x 262 x 39
• Cover type: Hardback
• Editor(s): Charles-Albert (Abu Dhabi Investment Authority) Lehalle