# What is the difference between regular PCA and probabilistic PCA?

I know regular PCA does not follow probabilistic model for observed data. So what is the basic difference between PCA and PPCA? In PPCA latent variable model contains for example observed variables $y$, latent (unobserved variables $x$) and a matrix $W$ that does not has to be orthonormal as in regular PCA. One more difference that I can think of regular PCA only provide principal components, where PPCA provides the probabilistic distribution of the data.

Could someone please through more light on the differences between PCA and PPCA?