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NuGet (pronounced "New Get") [3] is a package manager, primarily used for packaging and distributing software written using .NET and the .NET Framework. The Outercurve Foundation initially created it under the name NuPack.
PURLs allow third party control over both URL resolution and resource metadata provision. A URL is simply an address of a resource on the World Wide Web. A Persistent URL is an address on the World Wide Web that causes a redirection to another Web resource. If a Web resource changes location (and hence URL), a PURL pointing to it can be updated.
chocolatey.org Chocolatey [ 5 ] is a machine-level, command-line package manager and installer for software on Microsoft Windows . It uses the NuGet packaging infrastructure and Windows PowerShell to simplify the process of downloading and installing software.
NuGet is the package manager for all .NET platforms. It is used to retrieve third-party libraries into a .NET project with a global library feed at NuGet.org. [21] Private feeds can be maintained separately, e.g., by a build server or a file system directory. UML package diagram of the stream hierarchy in .NET
You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.
A uniform resource locator (URL), colloquially known as an address on the Web, [1] is a reference to a resource that specifies its location on a computer network and a mechanism for retrieving it. A URL is a specific type of Uniform Resource Identifier (URI), [ 2 ] [ 3 ] although many people use the two terms interchangeably.
ProGet currently supports a growing list of package managers, including NuGet, Chocolatey, Bower, npm, Maven, PowerShell, RubyGems, Helm for Kubernetes, Debian, Python, and Visual Studio Extensions (.vsix). ProGet also supports Docker containers, Jenkins build artifacts (through a plugin) and vulnerability scanning.
Infer.NET follows a model-based approach and is used to solve different kinds of machine learning problems including standard problems like classification, recommendation or clustering, customized solutions and domain-specific problems.