Microsoft.ML.CpuMath 3.0.0-preview.23266.6

The ID prefix of this package has been reserved for one of the owners of this package by Prefix Reserved
.NET 6.0 .NET Standard 2.0
This is a prerelease version of Microsoft.ML.CpuMath.
dotnet add package Microsoft.ML.CpuMath --version 3.0.0-preview.23266.6
NuGet\Install-Package Microsoft.ML.CpuMath -Version 3.0.0-preview.23266.6
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.
<PackageReference Include="Microsoft.ML.CpuMath" Version="3.0.0-preview.23266.6" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Microsoft.ML.CpuMath --version 3.0.0-preview.23266.6
#r "nuget: Microsoft.ML.CpuMath, 3.0.0-preview.23266.6"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install Microsoft.ML.CpuMath as a Cake Addin
#addin nuget:?package=Microsoft.ML.CpuMath&version=3.0.0-preview.23266.6&prerelease

// Install Microsoft.ML.CpuMath as a Cake Tool
#tool nuget:?package=Microsoft.ML.CpuMath&version=3.0.0-preview.23266.6&prerelease

Microsoft.ML.CpuMath contains optimized math routines for ML.NET.

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 is compatible.  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. 
.NET Core netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen40 was computed.  tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Additional computed target framework(s)
Learn more about Target Frameworks and .NET Standard.
  • .NETStandard 2.0

  • net6.0

    • No dependencies.

NuGet packages (3)

Showing the top 3 NuGet packages that depend on Microsoft.ML.CpuMath:

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

ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.

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

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


Application Component for the Alliance Business Suite.

GitHub repositories (3)

Showing the top 3 popular GitHub repositories that depend on Microsoft.ML.CpuMath:

Repository Stars
PiP tool is a software to use the Picture in Picture mode on Windows. This feature allows you to watch content (video for example) in thumbnail format on the screen while continuing to use any other software on Windows.
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.
An Ambilight clone for Windows based sources - HTPC or just a normal PC
Version Downloads Last updated
3.0.0-preview.23266.6 13,503 5/17/2023
3.0.0-preview.22621.2 7,651 12/22/2022
2.0.1 322,501 2/1/2023
2.0.1-preview.22573.9 2,474 11/24/2022
2.0.0 148,535 11/8/2022
2.0.0-preview.22551.1 341 11/1/2022
2.0.0-preview.22313.1 12,450 6/14/2022
2.0.0-preview.22310.1 298 6/11/2022
1.7.1 955,721 3/9/2022
1.7.0 371,779 11/9/2021 1,172 10/22/2021
1.6.0 468,600 7/15/2021
1.5.5 381,301 3/4/2021
1.5.4 114,166 12/17/2020
1.5.2 306,278 9/11/2020
1.5.1 81,314 7/11/2020
1.5.0 131,552 5/26/2020
1.5.0-preview2 55,719 3/12/2020
1.5.0-preview 65,902 12/26/2019
1.4.0 454,785 11/5/2019
1.4.0-preview2 26,652 10/8/2019
1.4.0-preview 60,557 8/30/2019
1.3.1 154,968 8/6/2019
1.2.0 74,530 7/3/2019
1.1.0 35,286 6/4/2019
1.0.0 147,271 5/2/2019
1.0.0-preview 19,132 4/2/2019
0.11.0 34,329 3/5/2019
0.10.0 41,901 2/5/2019
0.9.0 33,924 1/8/2019
0.8.0 18,947 12/4/2018
0.7.0 25,630 11/6/2018
0.6.0 16,644 10/2/2018
0.5.0 8,438 9/5/2018
0.4.0 64,142 8/7/2018