How to learn Gaussian Process' [R][reddit]/r/MachineLearning
I recently began a project where I am predicting object translations due to manipulation by a robotic arm. Because of the inconsistent nature of the real world, the predictor needs to show that there is a probabilistic distribution of outputs for every input. I have forced some math and concepts in my head from watching Youtube and research papers that are far beyond my scope. Most of what I'm doing is wasting time going back and fourth from reading about GP's to covariance functions. I really just need to find a place to start. My gut is telling me to learn the mathematics first then try to code something, but I learned deep learning the other way around and that worked out. If any geniuses out there have some advice or even just resources that would awesome. If I find anything myself I'll share it here.