I am trying to learn machine learning and as a novice in the field of statistics, I am having a hard time while trying to read pattern recognition and machine learning by Bishop. I have already watched Andrew Ng's course on machine learning but now I want to get a mathematical point of view .
My problem is that I don't understand many gaussian processes mentioned in the book such as bayesian inference of gaussian , conditional and marginal gaussian ,etc. I have already tried to search for some resources but found none which were to the point.
So, is there any good resource which covers mathematical background (specially probability and distributions) required for machine learning ?