Data Analysis and Machine Learning: Elements of Bayesian theory and Bayesian Neural Networks
  • Contents
    • Why Bayesian Statistics?
    • Inference
    • Statistical Inference
    • Some history
    • The Bayesian recipe
    • Bayes' theorem
    • The friends of Bayes' theorem
    • Inference With Parametric Models
    • Illustrative examples with python code
    • Example: Is this a fair coin?
    • A few words on different priors
    • Bayesian parameter estimation (single parameter)
    •    Example: Measured flux from a star
    •    Simple Photon Counts: Frequentist Approach
    •    Simple Photon Counts: Bayesian Approach
    •    A note about priors
    •    Simple Photon Counts: Bayesian approach in practice
    •    Best estimates and confidence intervals
    •    Simple Photon Counts: Best estimates and confidence intervals
    • Bayesian parameter estimation (multiple parameters, covariance)
    • Bayesian model selection

 

 

 





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