NumSharp 0.10.4
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.
Showing the top 20 packages that depend on NumSharp.
| Packages | Downloads |
|---|---|
|
TensorFlow.NET
Google's TensorFlow full binding in .NET Standard.
Building, training and infering deep learning models.
https://tensorflownet.readthedocs.io
|
11 |
|
TensorFlow.NET
Google's TensorFlow full binding in .NET Standard.
Building, training and infering deep learning models.
https://tensorflownet.readthedocs.io
|
10 |
|
TensorFlow.NET
Google's TensorFlow full binding in .NET Standard.
Docs: https://tensorflownet.readthedocs.io
|
10 |
|
TensorFlow.NET
Google's TensorFlow full binding in .NET Standard.
Docs: https://tensorflownet.readthedocs.io
|
9 |
|
TensorFlow.NET
Google's TensorFlow full binding in .NET Standard.
Building, training and infering deep learning models.
https://tensorflownet.readthedocs.io
|
9 |
|
TensorFlow.NET
TensorFlow binding for .NET Standard.
|
7 |
|
TensorFlow.NET
Google's TensorFlow full binding in .NET Standard.
Docs: https://tensorflownet.readthedocs.io
|
7 |
|
TensorFlow.NET
Google's TensorFlow binding in .NET Standard.
Docs: https://tensorflownet.readthedocs.io
|
5 |
Main changes since v0.10
1: Fix byte to float converting.
2: Fix np.astype copy.
3: Support axis for np.argmax.
4: Slice NDArray is avaliable.
5: Speed up by adding Span<T> for indexing.
6: Fix np.sum -1 axis.
7: Fix np.meshgrid.
8: Add np.expand_dims.
9: Add nd.negative/ nd.positive.
10: Add nd.negate.
11: Fix mgrid.
.NET Standard 2.0
- ArrayFire (>= 0.0.2)
- System.Memory (>= 4.5.3)
- System.Numerics.Vectors (>= 4.5.0)
| Version | Downloads | Last updated |
|---|---|---|
| 0.30.0 | 8 | 04/18/2025 |
| 0.20.5 | 7 | 04/19/2025 |
| 0.20.4 | 7 | 04/19/2025 |
| 0.20.3 | 7 | 04/18/2025 |
| 0.20.2 | 7 | 04/18/2025 |
| 0.20.1 | 7 | 04/18/2025 |
| 0.20.0 | 7 | 04/18/2025 |
| 0.10.6 | 7 | 04/19/2025 |
| 0.10.5 | 7 | 04/19/2025 |
| 0.10.4 | 6 | 04/19/2025 |
| 0.10.3 | 7 | 04/18/2025 |
| 0.10.2 | 7 | 04/18/2025 |
| 0.10.1 | 7 | 04/18/2025 |
| 0.10.0 | 7 | 04/18/2025 |
| 0.9.0 | 7 | 04/18/2025 |
| 0.8.3 | 7 | 04/18/2025 |
| 0.8.2 | 7 | 04/18/2025 |
| 0.8.1 | 7 | 04/18/2025 |
| 0.8.0 | 7 | 04/18/2025 |
| 0.7.4 | 6 | 04/18/2025 |
| 0.7.3 | 7 | 04/18/2025 |
| 0.7.2 | 7 | 04/18/2025 |
| 0.7.1 | 7 | 04/18/2025 |
| 0.7.0 | 7 | 04/18/2025 |
| 0.6.6 | 7 | 04/19/2025 |
| 0.6.5 | 7 | 04/19/2025 |
| 0.6.4 | 6 | 04/19/2025 |
| 0.6.3 | 7 | 04/18/2025 |
| 0.6.2 | 6 | 04/18/2025 |
| 0.6.1 | 7 | 04/18/2025 |
| 0.6.0 | 8 | 04/18/2025 |
| 0.5.0 | 7 | 04/18/2025 |
| 0.4.0 | 7 | 04/18/2025 |
| 0.3.0 | 7 | 04/18/2025 |
| 0.2.0 | 7 | 04/18/2025 |
| 0.1.0 | 7 | 04/18/2025 |