I used go in machine learning contexts extensively while writing graphpipe[1]. Go is a fantastic language for servers, and distributed communication. Unfortunately, the lack of generics and dependence on interfaces and reflection makes writing things that deal with multidimensional arrays pretty terrible. See, for example, the janky conversion code in graphpipe-go[2] to convert a multidimensional slice into contiguous row-major arrays. Also, libraries that try to create a numpy eqivalent end up with uncomfortable interfaces due to inability to overload operators. I agree with some of the sibling comments that go 2 will help but probably won't make things particularly pleasurable. Rust would be a more interesting route but definitely doesn't have the adoption of go.

[1] https://oracle.github.io/graphpipe

[2] https://github.com/oracle/graphpipe-go/blob/master/helpers.g...