NumSharp 0.6.6

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There is a newer version of this package available.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 0.6.6
dotnet add package NumSharp --version 0.6.6
<PackageReference Include="NumSharp" Version="0.6.6" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add NumSharp --version 0.6.6
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Release Notes

add NDArray to ValueType

Showing the top 5 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 Tensor in .NET, keep APIs same as NumPy and SciPy.
SciSharp/SiaNet
A C# deep learning library, human friendly, CUDA/OpenCL supported, well structured, easy to extend
SciSharp/Pandas.NET
Pandas port in C#, data analysis tool.

Version History

Version Downloads Last updated
0.10.4 44 7/18/2019
0.10.3 658 6/15/2019
0.10.2 333 5/25/2019
0.10.1 554 5/11/2019
0.10.0 245 5/5/2019
0.9.0 533 4/15/2019
0.8.3 339 3/29/2019
0.8.2 302 3/25/2019
0.8.1 146 3/22/2019
0.8.0 497 3/12/2019
0.7.4 208 3/7/2019
0.7.3 567 2/20/2019
0.7.2 145 2/18/2019
0.7.1 179 2/12/2019
0.7.0 220 1/28/2019
0.6.6 176 1/26/2019
0.6.5 229 1/11/2019
0.6.4 177 1/7/2019
0.6.3 198 12/30/2018
0.6.2 305 12/27/2018
0.6.1 156 12/26/2018
0.6.0 213 12/21/2018
0.5.0 264 12/5/2018
0.4.0 170 11/21/2018
0.3.0 186 11/7/2018
0.2.0 340 10/29/2018
0.1.0 202 10/10/2018
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