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Masterseminar in Data Science and Machine Learning

Masterseminar in Data Science and Machine Learning
type: Seminar (S)
semester: SS 2020
time: 2020-04-23
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2


2020-04-30
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2

2020-05-07
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2

2020-05-14
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2

2020-05-28
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2

2020-06-04
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2

2020-06-18
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2

2020-06-25
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2

2020-07-02
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2

2020-07-09
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2

2020-07-16
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2

2020-07-23
15:45 - 17:15 wöchentlich
20.30 SR -1.015 (UG)
20.30 Kollegiengebäude Mathematik, Englerstr. 2


lecturer: Prof. Dr. Andreas Geyer-Schulz
sws: 2
lv-no.: <a target="lvn" href="https://campus.studium.kit.edu/events/AX5PheNXRriF_32uWUbcuA">2540510</a>
Bibliography

Literature:

  • Goodfellow, I., Bengio, Y., & Courville, A. (2017). Deep Learning. MIT Press.
  • Jean, N., Burke, M., Xie, M., Davis, W. M., Lobell, D. B., & Ermon, S. (2016). Combining satellite imagery and machine learning to predict poverty. Science, 353(6301), 790-794.
  • LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444.
  • Leskovec, J., Rajaraman, A., & Ullman, J. D. (2014). Mining of Massive Datasets. Cambridge University Press.
  • Lopez De Prado, M. (2018). Advances in Financial Machine Learning. John Wiley & Sons
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