MathNet.Numerics.Data.Text 5.0.0

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

.NET 5.0 .NET Standard 2.0 .NET Framework 4.6.1

dotnet add package MathNet.Numerics.Data.Text --version 5.0.0

NuGet\Install-Package MathNet.Numerics.Data.Text -Version 5.0.0

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="MathNet.Numerics.Data.Text" Version="5.0.0" />

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

paket add MathNet.Numerics.Data.Text --version 5.0.0

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

#r "nuget: MathNet.Numerics.Data.Text, 5.0.0"

#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 MathNet.Numerics.Data.Text as a Cake Addin
#addin nuget:?package=MathNet.Numerics.Data.Text&version=5.0.0

// Install MathNet.Numerics.Data.Text as a Cake Tool
#tool nuget:?package=MathNet.Numerics.Data.Text&version=5.0.0

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

Text Data Input/Output Extensions for Math.NET Numerics, the numerical foundation of the Math.NET project, aiming to provide methods and algorithms for numerical computations in science, engineering and every day use.

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.

.NETFramework 4.6.1
- MathNet.Numerics (>= 5.0.0)
.NETFramework 4.8
- MathNet.Numerics (>= 5.0.0)
.NETStandard 2.0
- MathNet.Numerics (>= 5.0.0)
net5.0
- MathNet.Numerics (>= 5.0.0)
net6.0
- MathNet.Numerics (>= 5.0.0)

NuGet packages (5)

Showing the top 5 NuGet packages that depend on MathNet.Numerics.Data.Text:

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andrefmello91.ReinforcedConcreteMembrane Library for nonlinear analysis of reinforced concrete membrane elements by Modified Compression Field Theory (VECCHIO; COLLINS, 1986) and Disturbed Stress Field Model (VECCHIO, 2000)..	4.8K
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PhilipsTang.Mathlib PhilipsTang.Mathlib .NETStandard 2.0	444
NeuralNet NeuralNet is a neural network library that is great both for a beginner looking to get started quickly, and a technical expert wishing to implement their own features.	224

GitHub repositories (1)

Showing the top 1 popular GitHub repositories that depend on MathNet.Numerics.Data.Text:

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.	232

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.

232

Version	Downloads	Last updated
5.0.0	7,003	4/3/2022
5.0.0-beta02	96	4/3/2022
5.0.0-beta01	114	3/6/2022
5.0.0-alpha16	91	2/27/2022
5.0.0-alpha15	86	2/27/2022
5.0.0-alpha14	84	2/27/2022
5.0.0-alpha13	86	2/27/2022
5.0.0-alpha12	86	2/27/2022
5.0.0-alpha11	88	2/27/2022
5.0.0-alpha10	87	2/19/2022
5.0.0-alpha09	91	2/13/2022
5.0.0-alpha08	124	12/23/2021
5.0.0-alpha07	112	12/19/2021
5.0.0-alpha06	110	12/19/2021
5.0.0-alpha05	112	12/19/2021
5.0.0-alpha04	113	12/19/2021
5.0.0-alpha03	123	12/5/2021
5.0.0-alpha02	263	7/11/2021
5.0.0-alpha01	249	6/27/2021
4.1.0	10,992	12/30/2020
4.0.0	32,393	2/14/2018
4.0.0-beta01	834	2/4/2018
3.2.1	3,454	4/29/2017
3.2.0	4,645	4/11/2016
3.1.1	6,734	7/13/2015
3.1.0	2,053	1/11/2015
3.0.0	2,005	7/23/2014
3.0.0-beta02	929	6/15/2014
3.0.0-beta01	958	4/23/2014
3.0.0-alpha9	993	3/29/2014
3.0.0-alpha8	969	2/26/2014
3.0.0-alpha7	913	12/30/2013
3.0.0-alpha6	969	12/3/2013
3.0.0-alpha5	1,010	11/15/2013
3.0.0-alpha4	942	9/23/2013
1.1.0	2,145	6/23/2013

COMPATIBILITY: net5.0, net48 better supported with explicit builds
COMPATIBILITY: netstandard1.x, net40, net45 no longer supported
BREAKING: drop all which was marked as obsolete
BREAKING: all native provider adapters moved out to separate NuGet packages
BREAKING: switch many usages of tuples to value tuples (experimental)
Linear Algebra: Fix sparse inplace pointwise multiplication and division ~jkalias
Distributions: Logistic ~Bobby Ingram
Distributions: Perf: Cauchy avoid duplicate evaluation ~Febin
Random: NextBigIngegerSequence ~Silver-Fang
Random: xoshiro256StarStar fix out of range exception ~Charlie Turndorf
Precision: Perf: pre-compute negative powers ~Febin
Optimizations: Remove static properties in LevenbergMarquardtMinimizer ~Jong Hyun Kim
Root Finding: Newton-Raphson better handling of zero-evaluations
Fit.Curve and FindMinimum extended to accept two more parameters
Fixed an index out of bounds issue when calculating BFGS minimizer with one variable ~Shiney
Fixed Sparse COO NormalizeDuplicates ~Mohamed Moussa
Marcum-Q and Log1p functions ~CHUTORO
Series: stable series summation
Cubic Spline: Extrema and Stationary Points ~Eduardo Rojas
Statistics: Weighted Descriptive and Running Statistics ~Richard Allen
Providers: binary names and loading changes to follow conventions and better x-plat
Providers: drop managed reference linear algebra provider
Providers: native providers no longer inherit managed providers, managed now sealed
Providers: MKL provider compilation switched to Intel oneAPI MKL
Providers: support for provider packages with runtime folders
Better support for System.Text.Json: Polynomial, DescriptiveStatistics ~Joseph Petersen
Lots of internal cleanup, leveraging newer language features
Data: now released always together with Numerics (no longer separate versioning)
Control.Describe now includes CPU architecture and family identifier if know

MathNet.Numerics.Data.Text 5.0.0

.NETFramework 4.6.1

.NETFramework 4.8

.NETStandard 2.0

net5.0

net6.0

NuGet packages (5)

GitHub repositories (1)