Bibliography | Literature:
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Shortdescription | The volume, variety, and velocity of available data in finance have increased in recent years, and the available datasets present several new challenges in empirical applications and need new techniques for analysis. As a powerful technique for big data analysis, deep learning has recently been successfully utilized in several big data domains such as image processing, handwriting recognition, speech recognition, information extraction, management and control automation, and prediction. This seminar will cover some applications of big data and deep learning in finance. Topics: Genetic Programming Deep Learning for Natural Language Processing Deep Learning for Prediction Poverty Deep Learning for FOREX Market Prediction Deep Learning Tools Deep Learning and Linear Factor Models Deep Learning for Credit Risk Management Social Network and Financial Market Prediction Big Data Analytics in FinTech |
Masterseminar Big Data Mining in Finance
type: | Seminar (S) | ||
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semester: | SS 2019 | ||
time: | 2019-04-25 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-05-02 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-05-09 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-05-16 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-05-23 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-06-06 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-06-13 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-06-27 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-07-04 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-07-11 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-07-18 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 2019-07-25 15:45 - 17:15 wöchentlich 20.30 SR -1.015 (UG) 20.30 Kollegiengebäude Mathematik, Englerstr. 2 |
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lecturer: | Prof. Dr. Andreas Geyer-Schulz | ||
sws: | 2 | ||
lv-no.: | <a target="lvn" href="https://campus.studium.kit.edu/events/C8v2q6MlRYe0AJTqV5bRLw">2540510</a> | ||