If your ML model takes hours when it can take minutes, or takes days when it can take hours, you will move away. You could move away to another language or a faster interpreter but that's a different discussion.
How much of this is done in Python, vs constructing instructions in Python to run on a GPU at uber speed?
Widely used libraries for python such as SciPy, PyTorch, TensorFlow, Numpy all drop down to lower level languages (C/C++/Fortran).
I haven't seen many people doing ML in Python without one of these libraries, so I'd say it is mostly constructing instructions in Python and offloading the actual intensive work to these libraries (which may or may not run on GPU depending on your hardware).
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How much of this is done in Python, vs constructing instructions in Python to run on a GPU at uber speed?
Widely used libraries for python such as SciPy, PyTorch, TensorFlow, Numpy all drop down to lower level languages (C/C++/Fortran).
I haven't seen many people doing ML in Python without one of these libraries, so I'd say it is mostly constructing instructions in Python and offloading the actual intensive work to these libraries (which may or may not run on GPU depending on your hardware).