TensorFlow.jl
A Julia wrapper for TensorFlow (by malmaud)
FastAI.jl
Repository of best practices for deep learning in Julia, inspired by fastai (by FluxML)
| TensorFlow.jl | FastAI.jl | |
|---|---|---|
| 1 | 3 | |
| 879 | 584 | |
| - | 0.5% | |
| 0.0 | 4.0 | |
| almost 3 years ago | 2 months ago | |
| Julia | Julia | |
| GNU General Public License v3.0 or later | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
TensorFlow.jl
Posts with mentions or reviews of TensorFlow.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-06-16.
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Flux vs. TensorFlow
My understanding is that Tensorflow.jl does not wrap the Python library, but the underlying C implementation. So it was an alternative to the Python version, not just a wrapper of it, and this gave it some advantages: https://github.com/malmaud/TensorFlow.jl/blob/master/docs/src/why_julia.md
FastAI.jl
Posts with mentions or reviews of FastAI.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-08-03.
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Python vs Julia
You should definitely go with Julia. It has steeper learning curve than python, but it is way more powerful. As for the ecosystem, you shouldn't worry about that much: DataFrames.jl and friends is way better than pandas, MLJ.jl (https://github.com/alan-turing-institute/MLJ.jl) and FastAI.jl(https://github.com/FluxML/FastAI.jl) are great frameworks for regular ML and deepnet. And if at any point you get a feeling that you need some python library, you can always plug it in with PyCall.jl(https://github.com/JuliaPy/PyCall.jl).
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Flux vs. TensorFlow
Flux is nice, the API is very simple but it is lacking several utilities that PyTorch or TensorFlow have. Fortunately, [FastAI](https://github.com/FluxML/FastAI.jl) is adding these parts as a additional package. I hope very soon I could recommend the Deep Learning ecosystem in Julia without any doubt.
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Is Julia Ready for Deep Learning
There’s apparently an ongoing effort to port fast.ai v2 to Julia at https://github.com/FluxML/FastAI.jl - there some virtual standups on YouTube tracking progress, see https://youtu.be/3g0vjDA0PBU for example.
What are some alternatives?
When comparing TensorFlow.jl and FastAI.jl you can also consider the following projects:
Zygote.jl - 21st century AD
MLJ.jl - A Julia machine learning framework
julia - The Julia Programming Language
PyCall.jl - Package to call Python functions from the Julia language
Vulkan.jl - Using Vulkan from Julia
FiniteDiff.jl - Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support
model-zoo - Please do not feed the models
Metal.jl - Metal programming in Julia
AlphaZero.jl - A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.