Drones are being used in real world applications around the world! They can help detect anomalies in crop yields, provide companies with physical assets a real-time continuous data stream, and help secure locations by giving teams an aerial view. We'll learn how a dron can learn to navigate a novel, complex environment using an advanced reinforcement learning technique called Deep Deterministic Policy Gradients. Its a mixture of policy gradients and actor critic, I'll go through the dependencies before explaining the real algorithm. Enjoy!

Code for this video: https://github.com/llSourcell/Drone_Flight_Controller

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This video is apart of Move 37, my course at School of AI: https://theschool.ai/

Drone 3D Environment: https://rds.theconstructsim.com/signup/

More learning resources: https://pemami4911.github.io/blog/2016/08/21/ddpg-rl.html https://towardsdatascience.com/introduction-to-various-reinforcement-learning-algorithms-i-q-learning-sarsa-dqn-ddpg-72a5e0cb6287 https://coach.nervanasys.com/algorithms/policy_optimization/ddpg/index.html https://towardsdatascience.com/policy-gradients-in-a-nutshell-8b72f9743c5d https://deepmind.com/research/publications/deterministic-policy-gradient-algorithms/ https://medium.com/@kinwo/solving-continuous-control-environment-using-deep-deterministic-policy-gradient-ddpg-agent-5e94f82f366d https://medium.freecodecamp.org/an-introduction-to-policy-gradients-with-cartpole-and-doom-495b5ef2207f

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