Hi All,

I am currently taking graduate-level coursework in Stochastic Processes. My hope is to apply Stochastic Processes in Machine Learning. I have just started to think about uses cases, and one particular use case that stands out is having the machine learn which probability distribution to pick from when given a data set, then create "X" amount of random processes. 

As an amateur, I was wondering if anyone else has tried to use stochastic processes in machine learning. What use cases did you apply to? What were some best practices you can share?

Thanks,

Jacob