Microsoft.ML.OnnxTransformer 1.7.1

.NET Standard 2.0
There is a newer prerelease version of this package available.
See the version list below for details.
NuGet\Install-Package Microsoft.ML.OnnxTransformer -Version 1.7.1
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
dotnet add package Microsoft.ML.OnnxTransformer --version 1.7.1
<PackageReference Include="Microsoft.ML.OnnxTransformer" Version="1.7.1" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Microsoft.ML.OnnxTransformer --version 1.7.1
#r "nuget: Microsoft.ML.OnnxTransformer, 1.7.1"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. Copy this into the interactive tool or source code of the script to reference the package.
// Install Microsoft.ML.OnnxTransformer as a Cake Addin
#addin nuget:?package=Microsoft.ML.OnnxTransformer&version=1.7.1

// Install Microsoft.ML.OnnxTransformer as a Cake Tool
#tool nuget:?package=Microsoft.ML.OnnxTransformer&version=1.7.1

ML.NET component for Microsoft.ML.OnnxRuntime.Managed library

Product Versions
.NET net5.0 net5.0-windows net6.0 net6.0-android net6.0-ios net6.0-maccatalyst net6.0-macos net6.0-tvos net6.0-windows
.NET Core netcoreapp2.0 netcoreapp2.1 netcoreapp2.2 netcoreapp3.0 netcoreapp3.1
.NET Standard netstandard2.0 netstandard2.1
.NET Framework net461 net462 net463 net47 net471 net472 net48
MonoAndroid monoandroid
MonoMac monomac
MonoTouch monotouch
Tizen tizen40 tizen60
Xamarin.iOS xamarinios
Xamarin.Mac xamarinmac
Xamarin.TVOS xamarintvos
Xamarin.WatchOS xamarinwatchos
Compatible target framework(s)
Additional computed target framework(s)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (11)

Showing the top 5 NuGet packages that depend on Microsoft.ML.OnnxTransformer:

Package Downloads
Microsoft.ML.AutoML The ID prefix of this package has been reserved for one of the owners of this package by NuGet.org.

ML.NET AutoML: Optimizes an ML pipeline for your dataset, by automatically locating the best feature engineering, model, and hyperparameters

Microsoft.ML.DnnImageFeaturizer.AlexNet The ID prefix of this package has been reserved for one of the owners of this package by NuGet.org.

ML.NET component for pretrained AlexNet image featurization

Microsoft.ML.DnnImageFeaturizer.ResNet101 The ID prefix of this package has been reserved for one of the owners of this package by NuGet.org.

ML.NET component for pretrained ResNet101 image featurization

Microsoft.ML.DnnImageFeaturizer.ResNet50 The ID prefix of this package has been reserved for one of the owners of this package by NuGet.org.

ML.NET component for pretrained ResNet50 image featurization

Microsoft.ML.DnnImageFeaturizer.ResNet18 The ID prefix of this package has been reserved for one of the owners of this package by NuGet.org.

ML.NET component for pretrained ResNet18 image featurization

GitHub repositories (4)

Showing the top 4 popular GitHub repositories that depend on Microsoft.ML.OnnxTransformer:

Repository Stars
dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
microsoft/psi
Platform for Situated Intelligence
microsoft/CryptoNets
CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.
Azure/azure-stream-analytics
Azure Stream Analytics
Version Downloads Last updated
2.0.0-preview.22313.1 1,257 6/14/2022
1.7.1 26,562 3/9/2022
1.7.0 15,009 11/9/2021
1.7.0-preview.final 209 10/22/2021
1.6.0 18,024 7/15/2021
1.5.5 14,101 3/4/2021
1.5.4 6,765 12/17/2020
1.5.2 18,057 9/11/2020
1.5.1 11,365 7/11/2020
1.5.0 17,681 5/26/2020
1.5.0-preview2 9,649 3/12/2020
1.5.0-preview 5,698 12/26/2019
1.4.0 134,478 11/5/2019
1.4.0-preview2 3,613 10/8/2019
1.4.0-preview 3,507 8/30/2019
1.3.1 10,756 8/6/2019
1.2.0 21,859 7/3/2019
0.13.0 4,611 6/4/2019
0.12.0 2,697 5/2/2019
0.12.0-preview 1,395 4/2/2019
0.11.0 3,074 3/6/2019