Why write ML applications in Go?

There are libraries for other languages, especially Python, that are more complete than Go ML libraries and have benefited from years, if not decades, of research from the worlds brightest brains. Some Go programmers make the transition to Go in search of better performance, but because ML libraries are typically written in C and exposed to Python through their bindings, they do not suffer the same performance problems as interpreted Python programs. Deep learning frameworks such as TensorFlow and Caffe have very limited, if any, bindings to Go. Even with these issues in mind, Go is still an excellent, if not the best, language to develop an application containing ML components.