LG.MachineLearning
1.0.2
See the version list below for details.
dotnet add package LG.MachineLearning --version 1.0.2
NuGet\Install-Package LG.MachineLearning -Version 1.0.2
<PackageReference Include="LG.MachineLearning" Version="1.0.2" />
paket add LG.MachineLearning --version 1.0.2
#r "nuget: LG.MachineLearning, 1.0.2"
// Install LG.MachineLearning as a Cake Addin #addin nuget:?package=LG.MachineLearning&version=1.0.2 // Install LG.MachineLearning as a Cake Tool #tool nuget:?package=LG.MachineLearning&version=1.0.2
MachineLearning
MachineLearning is a .NET library mainly based on Microsoft ML.NET framework but it could be considered a melting pot of various frameworks (TensorFlow, TensorFlow models, PyTorch, Ultralytics YoloV5, etc...).<BR>
Main characteristics
- It's based on the ML.NET framework.<BR>
- All code can be written in any .NET standard languages (C#, F#, Basic, etc...) without knowledge or needs of resources as Python or anything other.
- It can be used with all .NET languages simply including the package on your project.<BR>
- It has a multitasking structure, providing base classes and which allow background models' train and update while using them for the inference without stopping; all in the same device.<BR>
- A growing model zoo with simple to use and parametrized classes to solve main machine learning tasks.<BR>
- It includes obviously all the ML.NET features at low level, but also wrapping some of them with more friendly classes for newbies.
- An object detection class (ObjectDetection.cs), having both train and inference skills, is provided to bridge the gap of the missing train feature task of the .NET projects, which nowadays is accomplished mainly in Python.
Getting started with MachineLearning
Simply include the package (or the reference to the project if you include it in your solution) to used the library.<BR> Include extra packages and runtimes if you need to use more advanced features.<BR>
Packages for advanced feature tasks:
- Onnx models inference: Onnx runtime or Onnx runtime GPU
- TensorFlow model inference: LG.TensorFlow.NET, LG.SciSharp.TensorFlow.Redist or LG.SciSharp.TensorFlow.Redist-Windows-GPU.
- TensorFlow object detection train: ODModelBuilderTF, ODModelBuilderTF-Redist-Win, ODModelBuilderTF-Redist-Win-TF
- Pytorch Yolo v5 train: work in progress...
Packages
LG.MachineLearning: the machine learning library.<BR>
License
ML.NET is licensed under the MIT license and it is free to use commercially.
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net5.0 is compatible. net5.0-windows was computed. net6.0 was computed. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 was computed. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 was computed. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. |
-
net5.0
- LG.Microsoft.ML.AutoML (>= 0.18.0.1)
- LG.Microsoft.ML.OnnxTransformer (>= 1.6.0.1)
- LG.Microsoft.ML.TimeSeries (>= 1.6.0.1)
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.