Blog - Bayesian Learning

P (θ | D) = \frac{P (θ, D)}{P (D)} = \frac{P (D | θ) P (θ)}{\sum_{θ^{'}} P (D | θ = θ^{'}) P (θ = θ^{'})}

Prior: $P (θ)$ .
Likelihood: $P (D | θ)$
Posterior: $P (θ | D)$ .
Marginal: $P (D | θ = θ^{'}) P (D)$
Joint Distribution: $P (θ, D)$