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I am highly thankful to various researchers to post various forms of information at different platforms (books, papers, presentation, social media, google, etc., that help in developing these presentations. The aim here is to provide information in most simple way to understand. I acknowledge the efforts of all.
Optimisation Algorithms:
Machine Learning:
Workshops:
Presentation:
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•Reinforcement Learning Markov Decision Process
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•Reinforcement Learning RL Algorithms
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•Reinforcement Learning Value Iteration
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•Reinforcement Learning Discounted Rewards
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•Reinforcement Learning Value Functions and Bellman Equation
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•Reinforcement Learning Value Iteration
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•Reinforcement Learning Policy Iteration
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•Reinforcement Learning Q Function
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•Reinforcement Learning SARSA and Q learning
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•Reinforcement Learning DQN (Deep Q Network)
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•Reinforcement Learning Double Deep Q Network (DDQN)
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•Reinforcement Learning Actor – Critic Algorithms
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•Reinforcement Learning Deep Deterministic Policy Gradient (DDPG)
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•Reinforcement Learning Advantage Actor Critic
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•Reinforcement Learning Asynchronous Advantage Actor Critic
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•Reinforcement Learning Trust Region Policy Optimization (TRPO)
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•Reinforcement Learning Proximal Policy Optimization (PPO)
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•Reinforcement Learning Soft Actor Critic (SAC)