Julia is a blast to do research on this stuff in, if you want to go beyond the basics like TensorFlow and PyTorch allows. The 2020's is going to be the decade of mixing numerical PDEs with machine learning IMO, and Julia already has a lot of features along these lines that are missing from "traditional ML" libraries.
Interesting.
I was going to go through their yearly conference talks to get an sense of Julia’s capabilities.
JuliaCon2019 etc on youtube. Is that the best way?
