NumSharp 0.6.2

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There is a newer version of this package available.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 0.6.2
dotnet add package NumSharp --version 0.6.2
<PackageReference Include="NumSharp" Version="0.6.2" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add NumSharp --version 0.6.2
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Release Notes

Added ReShape interface for Shape.
Added the water equation example.
Added np.mgrid API.
Add axis arg in ndarray.roll.

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/NumSharp
High Performance Computation for N-D Tensors in .NET, similar API to NumPy.
SciSharp/SiaNet
An easy to use C# deep learning library with CUDA/OpenCL support
SciSharp/Pandas.NET
Pandas port in C#, data analysis tool, process multi-dim array in DataFrame.

Read more about the GitHub Usage information on our documentation.

Version History

Version Downloads Last updated
0.20.5 2,687 12/31/2019
0.20.4 64,421 10/5/2019
0.20.3 763 9/28/2019
0.20.2 635 9/11/2019
0.20.1 11,261 9/1/2019
0.20.0 727 8/20/2019
0.10.6 14,990 7/24/2019
0.10.5 272 7/22/2019
0.10.4 241 7/18/2019
0.10.3 1,054 6/15/2019
0.10.2 408 5/25/2019
0.10.1 658 5/11/2019
0.10.0 365 5/5/2019
0.9.0 743 4/15/2019
0.8.3 409 3/29/2019
0.8.2 359 3/25/2019
0.8.1 218 3/22/2019
0.8.0 691 3/12/2019
0.7.4 272 3/7/2019
0.7.3 1,110 2/20/2019
0.7.2 207 2/18/2019
0.7.1 234 2/12/2019
0.7.0 287 1/28/2019
0.6.6 232 1/26/2019
0.6.5 293 1/11/2019
0.6.4 248 1/7/2019
0.6.3 256 12/30/2018
0.6.2 404 12/27/2018
0.6.1 216 12/26/2018
0.6.0 276 12/21/2018
0.5.0 333 12/5/2018
0.4.0 230 11/21/2018
0.3.0 251 11/7/2018
0.2.0 427 10/29/2018
0.1.0 295 10/10/2018
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