Welcome to part 4 of the Reinforcement Learning series as well our our Q-learning part of it. In this part, we're going to wrap up this basic Q-Learning by making our own environment to learn in. I hadn't initially intended to do this as a tutorial, it was just something I personally wanted to do, but, after many requests, it only makes sense to do it as a tutorial! Text-based tutorial and sample code: https://pythonprogramming.net/own-environment-q-learning-reinforcement-learning-python-tutorial/ Channel membership: https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ/join Discord: https://discord.gg/sentdex Support the content: https://pythonprogramming.net/support-donate/ Twitter: https://twitter.com/sentdex Instagram: https://instagram.com/sentdex Facebook: https://www.facebook.com/pythonprogramming.net/ Twitch: https://www.twitch.tv/sentdex #reinforcementlearning #machinelearning #python

Training a Unitree G1 to Walk w/ Reinforcement Learning
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Unitree G1 Security Disaster
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Testing VLMs and LLMs for robotics w/ the Jetson Thor devkit
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