Microsoft.ML.CpuMath 3.0.0-preview.22621.2

The ID prefix of this package has been reserved for one of the owners of this package by Prefix Reserved
.NET Core 3.1 .NET Standard 2.0
This is a prerelease version of Microsoft.ML.CpuMath.
dotnet add package Microsoft.ML.CpuMath --version 3.0.0-preview.22621.2
NuGet\Install-Package Microsoft.ML.CpuMath -Version 3.0.0-preview.22621.2
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.22621.2" />
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.22621.2
#r "nuget: Microsoft.ML.CpuMath, 3.0.0-preview.22621.2"
#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.22621.2&prerelease

// Install Microsoft.ML.CpuMath as a Cake Tool
#tool nuget:?package=Microsoft.ML.CpuMath&version=3.0.0-preview.22621.2&prerelease

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

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 net7.0 net7.0-android net7.0-ios net7.0-maccatalyst net7.0-macos net7.0-tvos net7.0-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 net481
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.
  • .NETCoreApp 3.1

    • No dependencies.
  • .NETStandard 2.0

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.22621.2 3,215 12/22/2022
2.0.1 35,417 2/1/2023
2.0.1-preview.22573.9 1,438 11/24/2022
2.0.0 86,962 11/8/2022
2.0.0-preview.22551.1 271 11/1/2022
2.0.0-preview.22313.1 8,964 6/14/2022
2.0.0-preview.22310.1 253 6/11/2022
1.7.1 670,864 3/9/2022
1.7.0 296,019 11/9/2021 1,113 10/22/2021
1.6.0 387,019 7/15/2021
1.5.5 332,569 3/4/2021
1.5.4 103,872 12/17/2020
1.5.2 262,405 9/11/2020
1.5.1 73,648 7/11/2020
1.5.0 117,383 5/26/2020
1.5.0-preview2 52,335 3/12/2020
1.5.0-preview 59,384 12/26/2019
1.4.0 412,534 11/5/2019
1.4.0-preview2 25,795 10/8/2019
1.4.0-preview 58,473 8/30/2019
1.3.1 136,084 8/6/2019
1.2.0 71,095 7/3/2019
1.1.0 32,567 6/4/2019
1.0.0 145,130 5/2/2019
1.0.0-preview 17,984 4/2/2019
0.11.0 32,724 3/5/2019
0.10.0 39,881 2/5/2019
0.9.0 29,275 1/8/2019
0.8.0 17,648 12/4/2018
0.7.0 24,587 11/6/2018
0.6.0 15,929 10/2/2018
0.5.0 7,947 9/5/2018
0.4.0 62,942 8/7/2018