Probability, Machine Learning, Statistics, Data Science, Artificial Intelligence.
likelihood is defined as the probability of observed data X as a function of θ. We can write that as L(θ) = P(θ; X=x). Here, X is known, but the parameter defining the distribution (θ) is unknown. In fact, the motivation for defining the likelihood is to determine the parameters of the