Artificial Intelligence in Finance: A Python-Based Guide
Yves Hilpisch
Venduto da Kennys Bookstore, Olney, MD, U.S.A.
Venditore AbeBooks dal 9 ottobre 2009
Nuovi - Brossura
Condizione: Nuovo
Quantità: 3 disponibili
Aggiungere al carrelloVenduto da Kennys Bookstore, Olney, MD, U.S.A.
Venditore AbeBooks dal 9 ottobre 2009
Condizione: Nuovo
Quantità: 3 disponibili
Aggiungere al carrello2020. Paperback. . . . . . Books ship from the US and Ireland.
Codice articolo V9781492055433
The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading.
Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book.
In five parts, this guide helps you:
Dr. Yves J. Hilpisch is founder and managing partner of The Python Quants (http://tpq.io), a group that focuses on the use of open source technologies for financial data science, algorithmic trading and computational finance. He is the author of the books Python for Finance (O'Reilly, 2014), Derivatives Analytics with Python (Wiley, 2015) and Listed Volatility and Variance Derivatives (Wiley, 2017). Yves lectures on computational finance at the CQF Program (http://cqf.com), on data science at htw saar University of Applied Sciences (http://htwsaar.de), and is the director for the online training program leading to the first Python for Finance University Certificate (awarded by htw saar).
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Quantità dell?ordine | Da 16 a 22 giorni lavorativi | Da 14 a 20 giorni lavorativi |
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