Yes. Numpy equivalents: Gonum (gonum.org) and/or Gorgonia Tensors (https://gorgonia.org/tensor https://gorgonia.org/tensor). Here's a cheatsheet for when to us

Yes. Numpy equivalents: Gonum (gonum.org) and/or Gorgonia Tensors (https://gorgonia.org/tensor https://gorgonia.org/tensor). Here's a cheatsheet for when to use what: https://www.cheatography.com/chewxy/cheat-sheets/data-science-in-go-a/ https://www.cheatography.com/chewxy/cheat-sheets/data-scienc... Pandas equivalents: gota (https://github.com/go-gota/gota https://github.com/go-gota/gota) or qframe (https://github.com/tobgu/qframe https://github.com/tobgu/qframe). I deploy deep learning models with Gorgonia (https://gorgonia.org/gorgonia https://gorgonia.org/gorgonia). I have found them to usually be faster than TensorFlow or PyTorch. CUDA is a bit iffy, but works, kinda. Distributed learning, you gotta build your own which is fairly straightforwards in the library. Compile them for your target. Move the binaries to your required server. Your CI/CD tool can do that easily