Automatic strong-name signing of referenced assemblies.
Utility software to strong-name sign .NET assemblies, including assemblies you do not have the source code for.
If you strong-name sign your own projects you may have noticed that if you reference an unsigned third party assembly you get an...
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Automatically creates a NuGet package from your project each time it builds. The NuGet package is placed in the project's output directory.
If you want to use a .nuspec file, place it in the same directory as the project's project file (e.g. .csproj, .vbproj, .fsproj).
This adds a PostBuildScripts...
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DiffSharp is an automatic differentiation (AD) library.
AD allows exact and efficient calculation of derivatives, by systematically invoking the chain rule of calculus at the elementary operator level during program execution. AD is different from numerical differentiation, which is prone to...
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DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/
Automatically force your ClickOnce app to update itself without prompting the user, making a less obtrusive end-user experience, and guaranteeing they are always using the latest version of the application.
Adds a post-build event to the project to run a PowerShell script that updates the ClickOnce...
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T4 Factories uses T4toolbox to automatically generate the source code for factory implementations and even contracts (if they don't exist already), based on a concrete class and a base interface.
It allows easier use of the factory pattern for easier unit testing and refactoring.
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/