Neural Networks Lectures Stanford
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.
The Elements of Statistical Learning
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