TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#. (by SciSharp)
F# Data
F# Data: Library for Data Access (by fsharp)
| TensorFlow.NET | F# Data | |
|---|---|---|
| 18 | 6 | |
| 3,112 | 804 | |
| 0.7% | 0.5% | |
| 8.6 | 6.8 | |
| about 1 month ago | 10 days ago | |
| C# | F# | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.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).
F# Data
Posts with mentions or reviews of F# Data.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-02-21.
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A new Excel add-in for custom functions and much more using F#. A replacement for VBA?
It is a brilliant tool for being able to import and export data in almost any format from your local computer, a database or across the web. For common data formats like csv, xml, and json, the Type Providers in FSharp.Data allow you automatically generate a type safe API against a sample file.
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Why learn Racket? A student's perspective
F# has this kind of stuff also, where it will dynamically type data dynamic sources like databases or rest calls, etc. for an example https://fsprojects.github.io/FSharp.Data/
- Twenty Years of C# with Anders Hejlsberg [audio]
- FSharp.Data: Data Access Made Simple
- FSharp.Data 4.1.1 Released
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F# Async Webrequest?
Have a look at the FSharp.Data library. It has bunch of cool stuff including Http.
What are some alternatives?
When comparing TensorFlow.NET and F# Data you can also consider the following projects:
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
Accord.NET
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.
NumSharp - High Performance Computation for N-D Tensors in .NET, similar API to NumPy.
numl - Machine Learning for .NET
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
Infer.NET - UAI 2015. Kernel-based just-in-time learning for expectation propagation