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: Get instant access to all my courses, including the new Prioritized Experience Replay course, with my subscription service. $29 a month gives you instant access to 42 hours of instructional content plus access to future updates, added monthly. Discounts available for Udemy students (enrolled longer than 30 days). Just send an email to [email protected] https://www.neuralnet.ai/courses Or, pickup my Udemy courses here: Deep Q Learning: https://www.udemy.com/course/deep-q-learning-from-paper-to-code/?couponCode=DQN-JUNE-22 Actor Critic Methods: https://www.udemy.com/course/actor-critic-methods-from-paper-to-code-with-pytorch/?couponCode=AC-JUNE-22 Curiosity Driven Deep Reinforcement Learning https://www.udemy.com/course/curiosity-driven-deep-reinforcement-learning/?couponCode=ICM-JUNE-22 Natural Language Processing from First Principles: https://www.udemy.com/course/natural-language-processing-from-first-principles/?couponCode=NLP-JUNE-22 Reinforcement Learning Fundamentals https://www.manning.com/livevideo/reinforcement-learning-in-motion Here are some books / courses I recommend (affiliate links): Grokking Deep Learning in Motion: https://bit.ly/3fXHy8W Grokking Deep Learning: https://bit.ly/3yJ14gT Grokking Deep Reinforcement Learning: https://bit.ly/2VNAXql Come hang out on Discord here: https://discord.gg/Zr4VCdv Need personalized tutoring? Help on a programming project? Shoot me an email! [email protected] Website: https://www.neuralnet.ai Github: https://github.com/philtabor Twitter: https://twitter.com/MLWithPhil