# A good way of building neural networks in both Julia and Python

**URL:** <https://discourse.julialang.org/t/a-good-way-of-building-neural-networks-in-both-julia-and-python/72064>\
**Category:** New to Julia\
**Tags:** flux, neural-network\
**Created:** [November 25, 2021, 1:52pm UTC](https://discourse.julialang.org/t/a-good-way-of-building-neural-networks-in-both-julia-and-python/72064 "2021-11-25T13:52:48Z")\
**Posts on this page:** 1\
**Showing post:** 5

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**Author:** ![Palli](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/palli/32/3380_2.png) [@Palli](https://discourse.julialang.org/u/Palli)\
**Post date:** [May 17, 2022, 10:46pm UTC](https://discourse.julialang.org/t/a-good-way-of-building-neural-networks-in-both-julia-and-python/72064/5 "2022-05-17T22:46:14Z")

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The answer might be different for building and using neural networks, and also different than for non-NN code.

In general, you want to choose one language for your main language, for the heavy lifting. That could be Julia (historically C and/or C++ and Fortran). You can basically do everything, including neural networks in Julia only.

I’m not sure if these might be helpful:

> **[Neural Network Exchange Format](https://en.wikipedia.org/wiki/Neural_Network_Exchange_Format)**
>
> Neural Network Exchange Format (NNEF) is an artificial neural network data exchange format developed by the Khronos Group. It is intended to reduce machine learning deployment fragmentation by enabling a rich mix of neural network training tools and inference engines to be used by applications across a diverse range of devices and platforms.
> NNEF was proposed in 2015 by member companies of the Khronos Group as a device and implementation independent transfer format capable of describing any arti...

> [@Triton: GPU Programming for Neural Networks](https://discourse.julialang.org/t/triton-gpu-programming-for-neural-networks/72033):
>
> Any thoughts on OpenAI’s [Triton](https://openai.com/blog/triton/)? @maleadt ?

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