If data science uses a lot of computational power, then why is python the most used programming language?

1

Julia

For example, Julia (https://julialang.org/) is arguably as high level as Python and is targeted to scientific computing and data science but it faster than C++ at execution in some circumstances (Julia compiles on the fly to native code via LLVM, a common compiler backend that is also used in many C/C++ compilers; the same compiler backend used by NVDIA to in the CUDA compiler https://developer.nvidia.com/cuda-llvm-compiler).

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Or, you can transform the Tensorflow model into one for Tensorflow Lite to be executed on an edge TPU (https://coral.ai/products/dev-board/) or GPU (https://www.nvidia.com/de-de/autonomous-machines/jetson-store/). Generally, you don't use python in these situation (although you could totally write your program in python on these boards, or even smaller stuff like micropython for microcontrollers and they can do NN as well (e.g. https://blog.tensorflow.org/2020/08/announcing-tensorflow-lite-micro-esp32.html most new embedded microcontrollers are adding NN ops and neural cores).

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