TensorFlow.NET
DiffSharp
| TensorFlow.NET | DiffSharp | |
|---|---|---|
| 18 | 2 | |
| 3,112 | 573 | |
| 0.7% | 0.9% | |
| 8.6 | 4.6 | |
| about 1 month ago | 16 days ago | |
| C# | F# | |
| Apache License 2.0 | BSD 2-clause "Simplified" License |
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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.NET
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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).
DiffSharp
- Automatic differentiation in a lot more than 38 lines of F#
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Neural Networks Fsharp
Yes. You can use TensorFlow.NET or DiffSharp.
What are some alternatives?
ML.NET - ML.NET is an open source and cross-platform machine learning framework for .NET.
dfdx - Deep learning in Rust, with shape checked tensors and neural networks
TorchSharp - A .NET library that provides access to the library that powers PyTorch.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
TensorFlowSharp - TensorFlow API for .NET languages
ocaml-torch - OCaml bindings for PyTorch
Accord.NET
corgi - A neural network, and tensor dynamic automatic differentiation implementation for Rust.
NumSharp - High Performance Computation for N-D Tensors in .NET, similar API to NumPy.
hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
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
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.