Python in ML acts as a glue language for loading the data, the interface, api, et. The hard work is done by C libraries running in parallel on GPUs.
Python is quite slow, and handles parallelization very badly. This is not very important for data loading and conditioning tasks, which would benefit little from parallelization, but it is critical for inference.
Python is quite slow, and handles parallelization very badly. This is not very important for data loading and conditioning tasks, which would benefit little from parallelization, but it is critical for inference.