Join us on June 27th for an exciting meetup! Quantopian's Director of Data Science, Dr. Thomas Wiecki, will be presenting "Bayesian Deep Learning: Dealing with Uncertainty & Non-Stationarity". As always we will be providing pizza & beer so don't miss out!
Bayesian Deep Learning: Dealing with Uncertainty & Non-Stationarity
Deep Learning continues to build out its dominance over other machine learning approaches on several challenging tasks including image, hand-writing, & speech recognition, image synthesis, as well as playing board & computer games exceeding human expert abilities.
This has generated a lot of interest in the quant finance community to try & mirror Deep Learning's success in the domain of algorithmic trading. Unfortunately, algorithmic trading poses a unique set of challenges. Specifically, the risk (i.e. uncertainty) of certain trading decisions as well as the fact that market behavior changes over time (i.e. non-stationarity) is not handled well by deep learning.
In this talk, I will show how we can embed Deep Learning in the Probabilistic Programming framework PyMC3 & elegantly solve these issues. Expressing neural networks as a Bayesian model naturally instills uncertainty in its predictions. This talk is focused on practitioners & will be introductory & hands-on with many code examples.
About the Speaker
Dr. Thomas Wiecki is Director of Data Science at Quantopian Inc, where he uses Probabilistic Programming & Machine Learning to solve problems in quantitative finance.He has developed various open source projects, such asPyfolio-- a portfolio & risk analysis library, & PyMC3 a probabilistic programming framework written in Python.
Prior to joining Quantopian, Thomas did his PhD at Brown University where he developed Bayesian methods & Neural Networks to understand brain disorders.A recognized international speaker, he has given talks at conferences across the US, Europe, & Asia.
About Quantopian
Quantopian inspires talented people from around the world to write investment algorithms. They provide capital, data, education tools, & infrastructure to algorithm authors. Quantopian offers license agreements for algorithms that fit its investment strategy, & the licensing authors are paid based on their strategys individual performance. Quantopian provides everything a quant needs to create a strategy & profit from it. In the second quarter of this year, Quantopian expects to begin allocating external capital toward these strategies via a pooled investment vehicle.
For more information about Quantopian, please visit:https://www.quantopian.com/.
