Microsoft.ML.CpuMath
3.0.0-preview.22621.2
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
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#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
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
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
- System.Memory (>= 4.5.3)
NuGet packages (3)
Showing the top 3 NuGet packages that depend on Microsoft.ML.CpuMath:
| Package | Downloads |
|---|---|
|
Microsoft.ML
ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers. |
|
|
Microsoft.ML.AutoML
ML.NET AutoML: Optimizes an ML pipeline for your dataset, by automatically locating the best feature engineering, model, and hyperparameters |
|
|
FenixAlliance.ACL.Dependencies
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 |
|---|---|
|
LionelJouin/PiP-Tool
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.
|
|
|
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.
|
|
|
fabsenet/adrilight
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 |
| 1.7.0-preview.final | 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 |