Recomended Files

• Lecture 19 - Reward Model _ Linear Dynamical System _ Stanford CS229_ Machine Learning (Autumn 2018)(720P_HD).mp4

• Lecture 18 - Continous State MDP _ Model Simulation _ Stanford CS229_ Machine Learning (Autumn 2018)(720P_HD).mp4

• Lecture 17 - MDPs _ Value_Policy Iteration _ Stanford CS229_ Machine Learning Andrew Ng (Autumn2018)(480P).mp4

• Lecture 16 - Independent Component Analysis _ RL _ Stanford CS229_ Machine Learning (Autumn 2018)(720P_HD).mp4

• Lecture 15 - EM Algorithm _ Factor Analysis _ Stanford CS229_ Machine Learning Andrew Ng -Autumn2018(720P_HD).mp4

• Lecture 14 - Expectation-Maximization Algorithms _ Stanford CS229_ Machine Learning (Autumn 2018)(480P).mp4

• Lecture 13 - Debugging ML Models and Error Analysis _ Stanford CS229_ Machine Learning (Autumn 2018)(480P).mp4

• Lecture 12 - Backprop _ Improving Neural Networks _ Stanford CS229_ Machine Learning (Autumn 2018)(720P_HD).mp4

• Lecture 11 - Introduction to Neural Networks _ Stanford CS229_ Machine Learning (Autumn 2018)(480P).mp4

• Lecture 10 - Decision Trees and Ensemble Methods _ Stanford CS229_ Machine Learning (Autumn 2018)(480P).mp4