SkillsCast
Human-Level Control Through Deep Reinforcement Learning
SkillsCast
About the Speaker
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.