Human-Level Control Through Deep Reinforcement Learning
In this talk Skif will discuss his implementation of Deepmind's paper on Reinforcement Learning for Atari Games published by Nature. It is considered a landmark paper in Reinforcement Learning literature in which an RL agent received human level performance a number of Atari games.
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Human-Level Control Through Deep Reinforcement Learning
Skif Pankov
I work as a financial quantitative analyst; I have a background in statistics and economics. I am self-studying theoretical and practical aspects of reinforcement learning with the view of studying the subject at university at a post-graduate level. My day job involves a lot of programming (Python), as well as pushing for adoption of deep learning as a tool for financial analysis.
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SkillsCast
In this talk Skif will discuss his implementation of Deepmind's paper on Reinforcement Learning for Atari Games published by Nature. It is considered a landmark paper in Reinforcement Learning literature in which an RL agent received human level performance a number of Atari games.
YOU MAY ALSO LIKE:
Thanks to our sponsors
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About the Speaker
Human-Level Control Through Deep Reinforcement Learning
Skif Pankov
I work as a financial quantitative analyst; I have a background in statistics and economics. I am self-studying theoretical and practical aspects of reinforcement learning with the view of studying the subject at university at a post-graduate level. My day job involves a lot of programming (Python), as well as pushing for adoption of deep learning as a tool for financial analysis.