On 22th of December I watched videos of Machine learning lectures focused on Reinforcement Learning.
Lectuer: Associate Professor Andrew Ng, Stanford University
- Applications of Reinforcement Learning, Markov Decision Process (MDP), Defining Value & Policy Functions, Value Function, Optimal Value Function, Value Iteration, Policy Iteration (watch on YouTube)
- Generalization to Continuous States, Discretization & Curse of Dimensionality, Models/Simulators, Fitted Value Iteration, Finding Optimal Policy (watch on YouTube)
- Partially Observable MDPs (POMDPs), Policy Search, Reinforce Algorithm, Pegasus Algorithm, Pegasus Policy Search, Applications of Reinforcement Learning (watch on YouTube)
See other Andrew Ng’s Machine Learning courses.
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About
Master thesis of Lukáš Zdechovan,
Lukáš Zdechovan (Author)
a master degree student of Applied Informatics at Comenius University. Thesis is lead by docent Igor Farkaš.
[...] To get the best background in RL as possible I watched several lectures of Machine Learning at Stanford University. [...]
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