FsLab
TensorFlow.NET
Our great sponsors
FsLab | TensorFlow.NET | |
---|---|---|
- | 18 | |
4 | 3,112 | |
- | 1.5% | |
0.0 | 8.6 | |
almost 6 years ago | about 1 month ago | |
C# | ||
- | Apache License 2.0 |
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.
FsLab
We haven't tracked posts mentioning FsLab yet.
Tracking mentions began in Dec 2020.
TensorFlow.NET
-
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.
-
AI .NET
TensorFlow .Net
-
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
-
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?
-
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
-
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!
-
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
-
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
-
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?
Accord.NET
ML.NET - ML.NET is an open source and cross-platform machine learning framework for .NET.
Deedle - Easy to use .NET library for data and time series manipulation and for scientific programming
TorchSharp - A .NET library that provides access to the library that powers PyTorch.
R Provider - Access R packages from F#
TensorFlowSharp - TensorFlow API for .NET languages
Infer.NET - UAI 2015. Kernel-based just-in-time learning for expectation propagation
encog-dotnet-core
NumSharp - High Performance Computation for N-D Tensors in .NET, similar API to NumPy.
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.
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