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You could try Cython and Lush. An ML dialect for ML would have been nice, but doesn't exist.

Cython is a niche language for writing perf-critical bits inside your Python codebase. It's like C for people who don't want to learn C. At least that's how I treated it, when I had to write some stuff to make some numpy ops faster.

Cython is not in any real sense a replacement for a modern data/ml stack.

True but it's really nice way to get the benefit of type checking in Python.

Just like you, I had started using Cython for performance but then realized that I can discard a bulk of type errors if I used for type checking.

The other benefit is that the Python library ecosystem stays available.

As funny as it would be, ML isn't really a great fit for ML, I don't think.

That's true for current ML offerings.

However, I think an ML designed for machine learning would be nice, especially if the type system is extended to multidimensional arrays shapes. Pattern matching on array shapes would be rather nice. Ocaml style interactive mode for exploration and compiling for performance would be nice too.

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