Skip to content

magehrke/MLC

Repository files navigation

Machine Learning Collection

Basic Reinforcement Learning:

Dynamic Programming:

  • Value Iteration
  • Policy Iteration

Temporal-Difference Learning:

  • Q-Learning
  • SARSA

Policy Gradient Methods:

  • REINFORCE

Reference: Reinforcement Learning: An Introduction by Sutton and Barto.

Advanced Reinforcement Learning:

Nonparametric Methods:

  • Histograms
  • Kernel Density Estimators
  • Nearest Neighbours

Reference: Pattern Recognition And Machine Learning by Bishop.

Mixture Models and EM:

  • K-means Clustering
  • Mixtures of Gaussians
  • Alternative views of EM

Reference: Pattern Recognition And Machine Learning by Bishop.

Others / not categorized yet:

  • Gaussian Processes
  • Support Vector Machines
  • Bayesian Optimization
  • LQR
  • Mixed Integer Programming
  • OptNet

About

Machine Learning Collection

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages