Probabilistic Modeling

Most of the posts below are based on Prof. Alp Kucukelbir’s topic course on Machine Learning with Probabilistic Programming. Special thanks to his excellent teaching.

Topics

• Foundations
  • Frequentist vs Bayesian
  • Bayesian Parameter Estimation
  • Sampling from distribution
• MCMC
  • Metropolis–Hastings Algorithm
  • Gibbs Sampling
  • Hamiltonian Monte Carlo
  • MCMC Diagnostics
• Variational Inference
  • Variational Inference
  • Automatic Differentiation
  • Automatic Differentiation Variational Inference