1. Supervised learning

• 1.1. Generalized Linear Models
  • 1.1.1. Bayesian Linear Regression
  • 1.1.2. Bayesian Logistic regression
• 1.2. Gaussian Processes
  • 1.2.1. Gaussian Process Regression (GPR)
  • 1.2.2. Kernels for Gaussian Processes
    • 1.2.2.1. References
• 1.3. Naive Bayes
  • 1.3.1. Gaussian Naive Bayes
• 1.4. Neural network models (supervised)
  • 1.4.1. Multi-layer Perceptron
  • 1.4.2. Classification