Probabilistic Machine Learning

Why probabilistic ML?

  • Consistent estimation: guaranteed to benefit from large data sets
  • Interpretable model weights, interpretable latent space
  • Sufficient statistics: fast learning from arbitrary large data sets
  • Generative modelling: ready to sample new data, detect novelties, replace missing values
  • Probabilistic inference: report marginal probabilities for interesting sub-sets of variables, perform maximum a posteriori prediction
  • Expectation maximization: learn from missing data

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