A Data Science Central Community
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?