MathNet.Numerics.MKL.Win-x64 3.0.0-beta2 Prefix Reserved

.NET 5.0 .NET Standard 2.0 .NET Framework 4.6.1

This is a prerelease version of MathNet.Numerics.MKL.Win-x64.

There is a newer version of this package available.
See the version list below for details.

Install-Package MathNet.Numerics.MKL.Win-x64 -Version 3.0.0-beta2

dotnet add package MathNet.Numerics.MKL.Win-x64 --version 3.0.0-beta2

<PackageReference Include="MathNet.Numerics.MKL.Win-x64" Version="3.0.0-beta2" />

For projects that support PackageReference, copy this XML node into the project file to reference the package.

paket add MathNet.Numerics.MKL.Win-x64 --version 3.0.0-beta2

The NuGet Team does not provide support for this client. Please contact its maintainers for support.

#r "nuget: MathNet.Numerics.MKL.Win-x64, 3.0.0-beta2"

#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 MathNet.Numerics.MKL.Win-x64 as a Cake Addin
#addin nuget:?package=MathNet.Numerics.MKL.Win-x64&version=3.0.0-beta2&prerelease

// Install MathNet.Numerics.MKL.Win-x64 as a Cake Tool
#tool nuget:?package=MathNet.Numerics.MKL.Win-x64&version=3.0.0-beta2&prerelease

The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Intel oneAPI MKL native libraries for Math.NET Numerics on Windows.

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.

- MathNet.Numerics.Providers.MKL (>= 5.0.0-alpha08)

NuGet packages (5)

Showing the top 5 NuGet packages that depend on MathNet.Numerics.MKL.Win-x64:

Package	Downloads
Microsoft.Quantum.Research.Simulation Quantum research libraries for quantum simulation (non-commercial).	35.4K
CaptchaRecognition.AlgoCore Captcha Recognition for DE UI based on Nerual Nets	1.1K
NyaongNet.NyMath Nyaong C# Library Math	621
FSound Description	301
HTM.Net Hierarchical Temporal Memory (HTM)	263

GitHub repositories (2)

Showing the top 2 popular GitHub repositories that depend on MathNet.Numerics.MKL.Win-x64:

Repository	Stars
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.	204
jdermody/brightwire Bright Wire is an open source machine learning library for .NET with GPU support (via CUDA)	105

Repository

Stars

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.

204

jdermody/brightwire

Bright Wire is an open source machine learning library for .NET with GPU support (via CUDA)

105

Version	Downloads	Last updated
3.0.0	2,897	4/3/2022
3.0.0-beta3	1,361	2/19/2022
3.0.0-beta2	93	12/29/2021
3.0.0-beta1	68	12/23/2021
2.6.0-beta3	74	12/19/2021
2.6.0-beta2	83	12/9/2021
2.5.0	30,549	1/1/2021
2.4.0	13,325	5/22/2020
2.3.0	180,637	2/14/2018
2.2.0	32,914	10/30/2016
2.1.0	1,406	9/8/2016
2.0.0	7,267	9/26/2015
1.8.0	8,419	5/9/2015
1.7.0	2,393	12/31/2014
1.6.0	1,902	6/21/2014
1.5.0	924	6/15/2014
1.4.0	1,255	3/1/2014
1.3.0	1,564	5/1/2013
1.2.1	1,483	2/4/2013
1.2.0	1,011	2/3/2013

New binary names and package structure with runtime folders