Financial Data Science - Tsai, Alicia; Fracastoro, Giulia; Calafiore, Giuseppe; El Ghaoui, Laurent
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Erscheint vorauss. 30. Juni 2025
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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 will equip 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 decisions, with over 50 examples and case studies and hands-on Matlab and Python code. Explore cutting-edge techniques and tools in machine learning for financial data analysis, including…mehr

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Produktbeschreibung
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 will equip 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 decisions, with over 50 examples and case studies and hands-on Matlab and Python code. Explore cutting-edge techniques and tools in machine learning for financial data analysis, including deep learning and natural language processing. Accessible to readers without a specialized background in finance or machine learning, and including coverage of data representation and visualization, data models and estimation, principal component analysis, clustering methods, optimization tools, mean/variance portfolio optimization and financial networks, this is the ideal introduction for financial services professionals, and graduate students in finance and data science.
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Autorenporträt
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.