This is on page 133 of the book: https://www.deeplearningbook.org/contents/ml.html#pf10
In the above, it says that
the data set is directly observed and so is not random
If that data we observe is not random, wouldn't the probability of the data occurring equal to 1. And thus, the denominator of Bayes' theorem also be 1? That should be incorrect as we wouldn't be able to normalize the numerator (a likelihood) if we divide it by 1...
In Bayesian stats, are both the data AND parameters of the data generating process both considered random? The book seems to imply that the data is fixed. In Frequentist, seems like only the data is viewed to be random.