Final remarks

Bayesian Data Analysis in Python

Michal Oleszak

Machine Learning Engineer

What you know

Chapter 1: The Bayesian Way

  • Bayesian vs. frequentist approach
  • Probability theory & distributions
  • Updating beliefs with more data

 

Chapter 3: Bayesian Inference

  • A/B testing
  • Decision analysis
  • Forecasting & regression

 

Chapter 2: Bayesian Estimation

  • Grid approximation
  • Prior distributions
  • Reporting Bayesian results

Chapter 4: Bayesian Linear Regression

  • Markov Chain Monte Carlo (MCMC)
  • Fitting and interpreting models with pymc3
  • Bayesian data analysis: a case study
Bayesian Data Analysis in Python

More Bayes

  • Hierarchical models:

$y = \beta_0 + \beta_1x_1 + \beta_2x_2$

$\beta_2 = \beta_{20} + \beta_{21}x_3$

  • More regression (logistic, Poisson, ...)

  • Bayesian machine learning

 

Bayesian Data Analysis in Python

Congratulations and good luck!

Bayesian Data Analysis in Python

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