Reinforcement Learning with JAX is a comprehensive repository featuring tutorials, code examples, and projects for learning and implementing RL algorithms with JAX. It covers topics such as MDPs, Q-Learning, policy gradients, deep Q-networks, and model-based RL—ideal for both beginners and experts.
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Reinforcement Learning with JAX is a comprehensive repository featuring tutorials, code examples, and projects for learning and implementing RL algorithms with JAX. It covers topics such as MDPs, Q-Learning, policy gradients, deep Q-networks, and model-based RL—ideal for both beginners and experts.
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brunoleej/RL-with-JAX
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Reinforcement Learning with JAX is a comprehensive repository featuring tutorials, code examples, and projects for learning and implementing RL algorithms with JAX. It covers topics such as MDPs, Q-Learning, policy gradients, deep Q-networks, and model-based RL—ideal for both beginners and experts.
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