LostTech.NumPy 0.3.0-b1

This is a prerelease version of LostTech.NumPy.
dotnet add package LostTech.NumPy --version 0.3.0-b1
NuGet\Install-Package LostTech.NumPy -Version 0.3.0-b1
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="LostTech.NumPy" Version="0.3.0-b1" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add LostTech.NumPy --version 0.3.0-b1
#r "nuget: LostTech.NumPy, 0.3.0-b1"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install LostTech.NumPy as a Cake Addin
#addin nuget:?package=LostTech.NumPy&version=0.3.0-b1&prerelease

// Install LostTech.NumPy as a Cake Tool
#tool nuget:?package=LostTech.NumPy&version=0.3.0-b1&prerelease

.NET bindings for NumPy. Requires the actual Python with NumPy installed.

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 was computed.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
.NET Core netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen40 was computed.  tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (5)

Showing the top 5 NuGet packages that depend on LostTech.NumPy:

Package Downloads
LostTech.TensorFlow

FULL TensorFlow 2.5+ for .NET with Keras. Build, train, checkpoint, execute models. Samples: https://github.com/losttech/Gradient-Samples, https://github.com/losttech/YOLOv4, https://github.com/losttech/Siren Deep learning with .NET blog: https://ml.blogs.losttech.software/ Comparison with TensorFlowSharp: https://github.com/losttech/Gradient/#why-not-tensorflowsharp Comparison with TensorFlow.NET: https://github.com/losttech/Gradient/#why-not-tensorflow-net Allows building arbitrary machine learning models, training them, and loading and executing pre-trained models using the most popular machine learning framework out there: TensorFlow. All from your favorite comfy .NET language. Supports both CPU and GPU training (the later requires CUDA or a special build of TensorFlow). Provides access to full tf.keras, estimators and many more APIs. Free for non-commercial use. For licensing options see https://losttech.software/buy_gradient.html !!NOTE!! This version requires Python 3.x x64 to be installed with TensorFlow 2.5.x. See the official installation instructions in https://www.tensorflow.org/install/ (ensure you are installing version 2.5 to avoid hard-to-debug issues). Please, report any issues to https://github.com/losttech/Gradient/issues For community support use https://stackoverflow.com/ with tags (must be all 3 together) tensorflow, gradient, and .net. For support email contact@losttech.software . More information in NuGet package release notes and on the project web page: https://github.com/losttech/Gradient . TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

Gradient

FULL TensorFlow 1.15 for .NET with Keras. Build, train, checkpoint, execute models. Comparison with TensorFlowSharp: https://github.com/losttech/Gradient/#why-not-tensorflowsharp Comparison with TensorFlow.NET: https://github.com/losttech/Gradient/#why-not-tensorflow-net Allows building arbitrary machine learning models, training them, and loading and executing pre-trained models using the most popular machine learning framework out there: TensorFlow. All from your favorite comfy .NET language. Supports both CPU and GPU training (the later requires CUDA or a special build of TensorFlow). Provides access to full tf.keras and tf.contrib APIs, including estimators. This preview will expire. !!NOTE!! This version requires Python 3.x x64 to be installed with tensorflow or tensorflow-gpu 1.15. See the official installation instructions in https://www.tensorflow.org/install/ (ensure you are installing version 1.15 to avoid hard-to-debug issues). Please, report any issues to https://github.com/losttech/Gradient/issues For community support use https://stackoverflow.com/ with tags (must be all 3 together) tensorflow, gradient, and .net. For on-site/remote support for this preview email contact@losttech.software . More information in NuGet package release notes and at the project web page: https://github.com/losttech/Gradient .

LostTech.MLAgents.Environments

.NET bindings for Unity ML Agents

LostTech.NumPy.FSharp

F# helpers for LostTech.NumPy

LostTech.PyGym

.NET bindings for OpenAI Gym. Requires actual Python with Gym installed.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
0.3.0-b1 214 11/2/2022
0.3.0-a5 3,567 2/17/2022
0.2.2 11,359 12/22/2020
0.2.1 8,786 8/13/2020
0.2.0 655 6/26/2020
0.1.4 2,310 2/6/2020
0.1.1-a1 373 2/5/2020