Probability, Machine Learning, Statistics, Data Science, Artificial Intelligence.
defines the distribution F(X;θ). Now, the probability of a random variable X=x would be P(X=x) = F(x;θ). Note that here the parameter θ is known. However, we usually have the data (x) in the real world, and the parameter defining the distribution (θ) is unknown. Given the model F(X;θ), the