m2cgen
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies (by BayesWitnesses)
TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#. (by SciSharp)
Our great sponsors
| m2cgen | TensorFlow.NET | |
|---|---|---|
| 8 | 18 | |
| 2,707 | 3,112 | |
| 0.6% | 1.5% | |
| 0.0 | 8.6 | |
| 6 months ago | 30 days ago | |
| Python | C# | |
| MIT License | Apache License 2.0 |
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.
m2cgen
Posts with mentions or reviews of m2cgen.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-02.
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How to use python ML script in tauri?
Check out: https://github.com/BayesWitnesses/m2cgen
- EleutherAI announces it has become a non-profit
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Redis as a Database — Data Migration With RedisOM, RedisGears and Redlock
Notice that I’m using random values to populate the Sentiment field. You might compute the values for your fields based on other fields or actually use an ML model to perform the transformation. E.g. you could make use of m2cgen to transform trained models to pure python code and load them in **RedisGears **to be executed in a *GearsBuilder *instance. Another option is to pull out the big guns and go straight to RedisAI.
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Why isn’t Go used in AI/ML?
I wish that it was more common for model outputs to be converted the way bayeswitness does with mc2gen https://github.com/BayesWitnesses/m2cgen
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Use your decision tree model in your Javascript project today with m2cgen
And that’s it! All the magic in just two lines of code. I would like to thank the authors of the m2cgen library and encourage you to try it out.
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We use Rust for an opensource malware detection engine. It's great at detecting ransomwares and we want to share results and ideas with you.
I forgot to update the README. We just replaced RNN with xgboost that has a better f1 and is very quick, as the decision trees are translated to plain rust using m2cgen.
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Is data science/engineering in Rust practical, does it provide any benefit over Python, and what are the best crates?
Probably, as many frameworks come with a Rust support (or there are wrappers). Some models, like decision tree, can also be automatically translated to plain Rust (in my company we use m2cgen to translate xgboost models to plain rust code).
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Flutter Machine Learning App
These repositories on GitHub are good start I think: https://github.com/BayesWitnesses/m2cgen and https://github.com/vickylance/dart_nn
TensorFlow.NET
Posts with mentions or reviews of TensorFlow.NET.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-04.
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Sentiment analysis in c#
But to answer your question. I've run UNet in C#. I trained the data originally using python and used SciSharp to run the model using GPU for a solution more than 5 years ago.
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AI .NET
TensorFlow .Net
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The Ultimate Guide to Tech Stack for Indie Hackers in 2023
Yes, exactly. Since you will probably use scikit / tensorflow / pytorch with Python, you can call your model directly in a Django controller. Using other frameworks you will probably have to create a separate microservice with a model exposed via Rest API or use bindings like TensorFlow.NET
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Have anyone use ML Net for production?
Not even close , It is close to python's scikit learn , and it does not have it is own deep learning framework like tensorflow or pytorch , while there are some developers that are trying to implement tensorflow in dotnet , they are doing a good job at providing TensorFlow's low-level C++ API , However c# is not as good as python in manipulating data , there are tons of online materials for python's data science libraries like numpy , pandas , scikit learn , tensorflow , pytorch , quick bug fixes , even some support for unique cases .
- If you had to pick a library from another language (Rust, JS, etc.) that isn’t currently available in Python and have it instantly converted into Python for you to use, what would it be?
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Does anyone have any experience using ML.NET for forecasting?
But Ive actually been looking at TensorFlow.NET. Its uses .NET binding for TensorFlow machine learning library. Heres the GitHub page: https://github.com/SciSharp/TensorFlow.NET
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Does Microsoft use F# for any of its internal projects?
If you're pointing out that Tensorflow.NET is exciting (https://github.com/SciSharp/TensorFlow.NET), I agree!
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Is F# a viable language for machine learning akin to Python?
Looks like TensorFlow is callable directly from .NET. https://github.com/SciSharp/TensorFlow.NET
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Need help Understanding A Neural Net better [P]
Building neural nets from scratch is going to be really hard, for a lot of reasons that you're not even aware of yet. You're better off using preexisting machine learning frameworks. For example here's a library for using tensorflow in c#: https://github.com/SciSharp/TensorFlow.NET
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How to develop an applications with multiple programming language
Why don't you try this: https://www.nuget.org/packages/TensorFlow.NET/ (and maybe other nugets).
What are some alternatives?
When comparing m2cgen and TensorFlow.NET you can also consider the following projects:
Synapses - A group of neural-network libraries for functional and mainstream languages
ML.NET - ML.NET is an open source and cross-platform machine learning framework for .NET.
R Provider - Access R packages from F#
TorchSharp - A .NET library that provides access to the library that powers PyTorch.
gorse - Gorse open source recommender system engine
TensorFlowSharp - TensorFlow API for .NET languages
randomforest - Random Forest implementation in golang
Accord.NET
gago - :four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)
NumSharp - High Performance Computation for N-D Tensors in .NET, similar API to NumPy.
go-fann - Go bindings for FANN, library for artificial neural networks
AForge.NET - AForge.NET Framework is a C# framework designed for developers and researchers in the fields of Computer Vision and Artificial Intelligence - image processing, neural networks, genetic algorithms, machine learning, robotics, etc.