NumSharp 0.20.4

NumSharp is the fundamental library for scientific computing with .NET providing a similar API to python's numpy scientific library. NumSharp has full N-D, broadcasting and axis support.  If you want to use .NET to get started with machine learning, NumSharp will be your best tool.

Install-Package NumSharp -Version 0.20.4
dotnet add package NumSharp --version 0.20.4
<PackageReference Include="NumSharp" Version="0.20.4" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add NumSharp --version 0.20.4
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Release Notes

Support for np.newaxis and ellipsis (...) slicing. Added: np.transpose, np.swapaxes, ndarray.T, np.moveaxis, np.rollaxis, np.size, np.copyto, np.ceil, np.arccos, np.floor, np.modf, np.square, np.round, np.sign, np.arcsin, np.arctan, np.random.beta, np.random.gamma, np.random.bernoulli, np.random.binomial, np.random.lognormal, np.random.normal, np.random.poisson, np.random.chisquare, np.random.geometric.
Performance optimization for np.array, np.linspace, Randomizer class and all np.random.* methods.

Showing the top 5 GitHub repositories that depend on NumSharp:

Repository Stars
SciSharp/TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C#.
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.

Version History

Version Downloads Last updated
0.20.4 13,801 10/5/2019
0.20.3 593 9/28/2019
0.20.2 565 9/11/2019
0.20.1 10,568 9/1/2019
0.20.0 547 8/20/2019
0.10.6 13,837 7/24/2019
0.10.5 219 7/22/2019
0.10.4 196 7/18/2019
0.10.3 919 6/15/2019
0.10.2 378 5/25/2019
0.10.1 617 5/11/2019
0.10.0 319 5/5/2019
0.9.0 667 4/15/2019
0.8.3 375 3/29/2019
0.8.2 332 3/25/2019
0.8.1 189 3/22/2019
0.8.0 632 3/12/2019
0.7.4 243 3/7/2019
0.7.3 897 2/20/2019
0.7.2 181 2/18/2019
0.7.1 206 2/12/2019
0.7.0 259 1/28/2019
0.6.6 204 1/26/2019
0.6.5 263 1/11/2019
0.6.4 221 1/7/2019
0.6.3 233 12/30/2018
0.6.2 359 12/27/2018
0.6.1 190 12/26/2018
0.6.0 247 12/21/2018
0.5.0 303 12/5/2018
0.4.0 203 11/21/2018
0.3.0 222 11/7/2018
0.2.0 398 10/29/2018
0.1.0 248 10/10/2018