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CFEM Seminar - Title: "Deep Learning in Quantitative Finance" | Thomas Wiecki | Quantopian Inc.

Wednesday, Apr 26, 2017 at 6:00 PM until 7:15 PM [.ics]
CFEM - 55 Broad Street, 3rd Floor, New York, NY 10004 - Broadcast to Rhodes Hall 267

This event requires an RSVP.

Abstract:

Deep Learning has continued to take the Machine Learning world by storm. By continuing to dominate benchmark data sets of increasingly complex structure it has spawned huge interest in academia and industry alike. Especially recent advances in Recurrent Neural Networks which can model complex time-dependencies show great potential for advances in Algorithmic Trading. In this talk, I will give an introduction to deep learning, its recent developments, and how they relate to algorithmic trading.

Bio:

Dr. Thomas Wiecki is Director of Data Science at Quantopian Inc, where he uses Probabilistic Programming and Machine Learning to solve problems in quantitative finance.

Among other open source projects, he is involved in the development of PyMC3 — a probabilistic programming framework written in Python.

Thomas holds a PhD from Brown University. A recognized international speaker, he has given talks at conferences across the US, Europe, and Asia.

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