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Reinforcement Learning and Interpretability

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Content provided by The Quant / Financial Engineering Podcast and Patrick J Zoro. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Quant / Financial Engineering Podcast and Patrick J Zoro or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
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
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50 episodes

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Manage episode 320254265 series 2686124
Content provided by The Quant / Financial Engineering Podcast and Patrick J Zoro. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Quant / Financial Engineering Podcast and Patrick J Zoro or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
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
  continue reading

50 episodes

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