I wrote a lot of (and still occasionally maintain) a library called golearn [1] which tried to bring first-class support for the “traditional” ML algorithms, but it seems that Go’s compiler and toolchain just don’t optimise well enough for Go to be very competitive on performance for that application. That’s not a criticism of Go, it’s just that C/C++/FORTRAN have decades of optimising compiler support and most competing solutions are Python sugar over a nest of such C/C++/FORTRAN libraries. Go’s also concurrent, which is nice, but we found cases where being too concurrent also cost performance for most people. I’m still optimistic that Go has a place in ML, but it’s probably not right now.