Finance vs. Machine Learning

Data Science, Sutton Center / Sutton South (NY Hilton)
Average rating: ***..
(3.62, 8 ratings)

This talk is intended to explain how we can use tools coming from financial modeling in user-based models. These techniques are especially useful in the situation where the underlying signals are weak and we can’t expect a truly accurate model, which is mostly the case when forecasting the stock market.

Photo of Cathy O'Neil

Cathy O'Neil

Intent Media

Cathy O’Neil earned a Ph.D. in math from Harvard, was postdoc at MIT in the math department, and a professor at Barnard College where she published a number of research papers in arithmetic algebraic geometry. She then chucked it and switched over to the private sector. She worked as a quant for the hedge fund D.E. Shaw in the middle of the credit crisis, and then for RiskMetrics, a risk software company that assesses risk for the holdings of hedge funds and banks. Since this spring she’s been a data scientist for the startup media company “Intent Media”;


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