Deep Q Learning is Simple with PyTorch | Full Tutorial 2020

The PyTorch deep learning framework makes coding a deep q learning agent in python easier than ever. We're going to code up the simplest possible deep Q learning agent, and show that we only need a replay memory to get some serious results in the Lunar Lander environment from the Open AI Gym. We don't really need the target network, though it has been known to help the deep Q learning algorithm with convergence.

Learn how to turn deep reinforcement learning papers into code:

Deep Q Learning:
https://www.udemy.com/course/deep-q-learning-from-paper-to-code/?couponCode=DQN-JUNE-2021

Actor Critic Methods:
https://www.udemy.com/course/actor-critic-methods-from-paper-to-code-with-pytorch/?couponCode=AC-JUNE-2021

Natural Language Processing from First Principles:
https://www.udemy.com/course/natural-language-processing-from-first-principles/?couponCode=NLP1-JULY-2021
Reinforcement Learning Fundamentals
https://www.manning.com/livevideo/reinforcement-learning-in-motion

Come hang out on Discord here:
https://discord.gg/Zr4VCdv

Website: https://www.neuralnet.ai
Github: https://github.com/philtabor
Twitter: https://twitter.com/MLWithPhil

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