FastAI.jl
Repository of best practices for deep learning in Julia, inspired by fastai (by FluxML)
PyCall.jl
Package to call Python functions from the Julia language (by JuliaPy)
| FastAI.jl | PyCall.jl | |
|---|---|---|
| 3 | 28 | |
| 584 | 1,438 | |
| 0.5% | 0.3% | |
| 4.0 | 6.1 | |
| 2 months ago | about 2 months ago | |
| Julia | Julia | |
| MIT License | 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.
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.
-
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.
PyCall.jl
Posts with mentions or reviews of PyCall.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-06.
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I just started into Julia for ML
For point 3 you can use https://github.com/cjdoris/PythonCall.jl or https://github.com/JuliaPy/PyCall.jl (and their respective Python sister packages).
- The Mojo Programming Language: A Python Superset Drawing from Rust's Strengths
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Calling Chapel, Carbon, and zig code in Julia
PyCall.jl is really handy. Are there any similar projects for calling Chapel code, or Carbon/zig?
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Am I dumb in thinking I can use Rust as a Fast Python and leave it at that?
Julia and Python interop should not be a problem at all. Actually Julia has one of the best interops I’ve ever seen, so much that swift copied it. https://github.com/JuliaPy/PyCall.jl
- Which tools do you use for python + Data Science?
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I don't want to abandon Rust for Julia
One small note, julia also has great python interop via PyCall.jl
- Faster Python calculations with Numba: 2 lines of code, 13× speed-up
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Interoperability in Julia
It is possible to call Python from Julia using PyCall. Then to install PyCall, run the command in the Julia REPL.
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Why is Python so used in the machine learning?
That said, you can run python modules in Julia. So you can just export your code as a module and then use it in Julia via the PyCall package. short description here github here <— you’d just add the pacakge via the really nice package manager built into julia, but for link for more detailed documentation
- Use rust code in Python with pyo3
What are some alternatives?
When comparing FastAI.jl and PyCall.jl you can also consider the following projects:
MLJ.jl - A Julia machine learning framework
py2many - Transpiler of Python to many other languages
TensorFlow.jl - A Julia wrapper for TensorFlow
Revise.jl - Automatically update function definitions in a running Julia session
julia - The Julia Programming Language
model-zoo - Please do not feed the models
Genie.jl - 🧞The highly productive Julia web framework
AlphaZero.jl - A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.
are-we-fast-yet - Are We Fast Yet? Comparing Language Implementations with Objects, Closures, and Arrays
fast-ruby - :dash: Writing Fast Ruby :heart_eyes: -- Collect Common Ruby idioms.
libffi - A portable foreign-function interface library.