
Financial Data Science
$137.75
- Hardcover
414 pages
- Release Date
30 June 2025
Summary
Financial Data Science: From Fundamentals to Insights
Confidently analyze, interpret, and act on financial data with this practical introduction to the fundamentals of financial data science.
Master the fundamentals with step-by-step introductions to core topics, equipping you with a solid foundation for applying data science techniques to real-world, complex financial problems.
Extract meaningful insights as you learn how to use data to lead informed, data-driven de…
Book Details
ISBN-13: | 9781009432245 |
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ISBN-10: | 1009432249 |
Author: | Giuseppe Calafiore, Laurent El Ghaoui, Giulia Fracastoro, Alicia Tsai |
Publisher: | Cambridge University Press |
Imprint: | Cambridge University Press |
Format: | Hardcover |
Number of Pages: | 414 |
Release Date: | 30 June 2025 |
Weight: | 1.09kg |
Dimensions: | 262mm x 210mm |
About The Author
Giuseppe Calafiore
Giuseppe C. Calafiore is a Professor of Automatic Control at the Electronics and Telecommunications Department at Politecnico di Torino, where he coordinates the Control Systems and Data Science group, and a former Visiting Professor at the University of California, Berkeley, where he co-taught graduate courses in financial data science. He is a co-author of Optimization Models (2014), and a Fellow of the IEEE.
Laurent El Ghaoui is Vice-Provost of Research and Innovation, and Dean of Engineering and Computer Science, at Vin University. He is a former Professor of Electrical Engineering and Computer Science at the University of California, Berkeley, where he taught topics in data science and optimization models within the Haas Business School Master of Financial Engineering programme. He is a co-author of Optimization Models (2014).
Giulia Fracastoro is an Assistant Professor at the Electronics and Telecommunications Department at Politecnico di Torino. In 2017, she obtained her Ph.D. degree in Electronics and Telecommunications Engineering from Politecnico di Torino with a thesis on design and optimization of graph transform for image and video compression. Her main research interests are graph signal processing and neural networks on graph-structured data.
Alicia Y. Tsai is a Research Engineer at Google DeepMind. She obtained her Ph.D. in Computer Sciences from the University of California, Berkeley. Her main research interests are optimization, natural language processing, and machine learning. She is also a founding board member of the Taiwan Data Science Association and the founder of Women in Data Science (WiDS) Taipei.
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