Bayesian Data Analysis with PyMc¶

• Frequentist approach to learning:
  • Maximum Likelihood principle
  • Maximum Likelihood for regression and classification
• Introduction into Bayesian Inference with PyMc (Binominal and Beta distribution)
• Bayesian Data Analysis
• Categorical data / Multinomial distribution / Dirichlet Prior
• MCMC Sampling
• Applications, Examples:
  • A/B Testing
  • Global Warming
  • Bayesian Model Comparision: Sturmschäden
  • Bundesliga Preditor (Poisson Distribution)
  • Topic Models (Latent Dirichlet Allocation)