In this episode, we are joined by Kevin Zatloukal. Kevin teaches Computer Science at the University of Washington and has his Ph.D. in Computer Science from MIT. He previously was a programmer for both Microsoft and Google. He is also a member of O’Shaughnessy Asset Management’s Research Partner Program, where he has written two papers applying machine learning concepts to investing.
In the interview, we discuss:
- The basics of machine learning and some examples of how it is applied, including the different types of machine learning and some common algorithms;
- How machine learning can be used in fantasy football to identify players with the potential for success
- The application of decision stumps and clustering to value investing, and;
- The balance between intuition and empirical results.
Kevin’s Research with OSAM
ML & Investing Part 1: From Linear Regression to Ensembles of Decision Stumps
ML & Investing Part 2: Clustering
Follow Kevin on Twitter: @kczat
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