Machine Learning for Physicists (Lecture 8): Deep Reinforcement Learning

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Lecture 8: Reinforcement Learning: Policy Gradient with Neural Networks, Q Learning

Contents: more examples for policy gradient, neural-network-based policy gradient (“deep policy gradient”), AlphaGo, Q learning

Lecture series by Florian Marquardt: Introduction to deep learning for physicists. The whole series covers: Backpropagation, convolutional networks, autoencoders, recurrent networks, Boltzmann machines, reinforcement learning, and more.

This video on the official FAU channel:

Florian Marquardt

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This is nice, atleast if you don't take this course next semester, I can watch stuff here! 🤓

rajshreeswarnkar

You know Fast Transform fixed-filter-bank neural networks are a thing. They are based on the fast Hadamard transform which only needs nlog2(n) add subtract operations to complete.

hoaxuan

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