Reinforcement Learning and Interpretability

Patrick Zoro welcomes to his podcasts Hariom Tatsat author of the book "Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python 1st Edition", Bryan Yekelchik Lehigh MFE graduate and Zach Coriarty 4th Year, Bachelors of Science in Computer Science and Business at Lehigh University, Interested in data science and ML, LinkedIn: https://www.linkedin.com/in/zachary-coriarty/ They discuss their recent paper on "Deep Q-Network Interpertability: Applications to ETF Trading" https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3973146 https://www.svedbergopen.com/files/1643786733_(3)_IJAIML2021YH205248CR_(p_61-70).pdf