Reinforcement learning is an area of machine learning that involves taking right action to maximize reward in a particular situation. In this full tutorial course, you will get a solid foundation in reinforcement learning core topics.
The course covers Q learning, SARSA, double Q learning, deep Q learning, and policy gradient methods. These algorithms are employed in a number of environments from the open AI gym, including space invaders, breakout, and others. The deep learning portion uses Tensorflow and PyTorch.
The course begins with more modern algorithms, such as deep q learning and policy gradient methods, and demonstrates the power of reinforcement learning.
Then the course teaches some of the fundamental concepts that power all reinforcement learning algorithms. These are illustrated by coding up some algorithms that predate deep learning, but are still foundational to the cutting edge. These are studied in some of the more traditional environments from the OpenAI gym, like the cart pole problem.
๐ปCode: https://github.com/philtabor/Youtube-Code-Repository/tree/master/ReinforcementLearning
โญ๏ธ Course Contents โญ๏ธ
โจ๏ธ (00:00:00) Intro
โจ๏ธ (00:01:30) Intro to Deep Q Learning
โจ๏ธ (00:08:56) How to Code Deep Q Learning in Tensorflow
โจ๏ธ (00:52:03) Deep Q Learning with Pytorch Part 1: The Q Network
โจ๏ธ (01:06:21) Deep Q Learning with Pytorch part 2: Coding the Agent
โจ๏ธ (01:28:54) Deep Q Learning with Pytorch part
โจ๏ธ (01:46:39) Intro to Policy Gradients 3: Coding the main loop
โจ๏ธ (01:55:01) How to Beat Lunar Lander with Policy Gradients
โจ๏ธ (02:21:32) How to Beat Space Invaders with Policy Gradients
โจ๏ธ (02:34:41) How to Create Your Own Reinforcement Learning Environment Part 1
โจ๏ธ (02:55:39) How to Create Your Own Reinforcement Learning Environment Part 2
โจ๏ธ (03:08:20) Fundamentals of Reinforcement Learning
โจ๏ธ (03:17:09) Markov Decision Processes
โจ๏ธ (03:23:02) The Explore Exploit Dilemma
โจ๏ธ (03:29:19) Reinforcement Learning in the Open AI Gym: SARSA
โจ๏ธ (03:39:56) Reinforcement Learning in the Open AI Gym: Double Q Learning
โจ๏ธ (03:54:07) Conclusion
Course from Machine Learning with Phil. Check out his YouTube channel: https://www.youtube.com/channel/UC58v9cLitc8VaCjrcKyAbrw
—
Learn to code for free and get a developer job: https://www.freecodecamp.org
Read hundreds of articles on programming: https://medium.freecodecamp.org
source
