# [[Bayesian]] Neural Network - [[Bayesian Model Estimation]] - Generally we want to learn Joint [[Probability]] distribution $P(y|x)$ but this does not use the model parameters w - We need $P(w|D) = \frac{P(D|w)P(w)}{P(D)}$ - D is the labelled dataset - Model is now defined by structure and parameters - The parameters encode information about [[Uncertainty]] - Can be understood using [[Bayesian Predictive Posterior]]