NumSharp 0.8.1

NumSharp is the fundamental package for scientific computing with dot NET. It has implemented the arange, array, max, min, reshape, normalize, unique and random interfaces and so on. More and more interfaces will be added to the library gradually. If you want to use .NET to get started with machine learning, NumSharp will be your best tool library.

There is a newer version of this package available.
See the version list below for details.
Install-Package NumSharp -Version 0.8.1
dotnet add package NumSharp --version 0.8.1
<PackageReference Include="NumSharp" Version="0.8.1" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add NumSharp --version 0.8.1
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Release Notes

Add np.repeat

  • .NETStandard 2.0

    • No dependencies.

Showing the top 4 GitHub repositories that depend on NumSharp:

Repository Stars
SciSharp/BotSharp
The Open Source AI Chatbot Platform Builder in 100% C# Running in .NET Core with Machine Learning algorithm.
SciSharp/TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C#.
SciSharp/NumSharp
High Performance Computation for N-D Tensors in .NET, similar API to NumPy.
SciSharp/Pandas.NET
Pandas port in C#, data analysis tool.

Version History

Version Downloads Last updated
0.20.4 587 10/5/2019
0.20.3 477 9/28/2019
0.20.2 550 9/11/2019
0.20.1 8,454 9/1/2019
0.20.0 511 8/20/2019
0.10.6 12,619 7/24/2019
0.10.5 183 7/22/2019
0.10.4 189 7/18/2019
0.10.3 876 6/15/2019
0.10.2 372 5/25/2019
0.10.1 608 5/11/2019
0.10.0 309 5/5/2019
0.9.0 642 4/15/2019
0.8.3 369 3/29/2019
0.8.2 327 3/25/2019
0.8.1 185 3/22/2019
0.8.0 626 3/12/2019
0.7.4 239 3/7/2019
0.7.3 847 2/20/2019
0.7.2 176 2/18/2019
0.7.1 202 2/12/2019
0.7.0 255 1/28/2019
0.6.6 199 1/26/2019
0.6.5 260 1/11/2019
0.6.4 217 1/7/2019
0.6.3 229 12/30/2018
0.6.2 350 12/27/2018
0.6.1 188 12/26/2018
0.6.0 243 12/21/2018
0.5.0 298 12/5/2018
0.4.0 199 11/21/2018
0.3.0 218 11/7/2018
0.2.0 392 10/29/2018
0.1.0 242 10/10/2018
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