Some caution is warranted. Always keep in mind that estimating distributions from samples is very hard, in particular for multidimensional and continuous varia

Some caution is warranted. Always keep in mind that estimating distributions from samples is very hard, in particular for multidimensional and continuous variables. Sometimes even infinite samples do not suffice (I am not kidding). The good news is that there are interesting and relevant tasks (for example classification) where you do not need to know the distribution to solve the task optimally, although if you somehow managed to do so (find the distribution) you would be able to solve the task optimally. Or more succinctly, knowing the distribution is sufficient but not necessary for such tasks (small mercies)