In this series of tutorial talks we will be Deep Reinforcement Learning from start to finish - the tech powering self-playing Atari games, Alpha Go, problems in automatic control and more.
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In this series of tutorial talks we will be Deep Reinforcement Learning from start to finish - the tech powering self-playing Atari games, Alpha Go, problems in automatic control and more.
In Part 2 of the series we are covering powerful upgrades to the Q-Learning algorithm introduced in Part 1 of the Series, as well as motivate and discuss the use of function approximation including deep neural networks in Reinforcement.
This talk will be highly interactive with a number of live code demonstrations and a fully featured Jupyter Notebook.
If you did not attend previous events in this series be sure to check out the resources listed in those events - including slides, blog posts, etc.,
