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NuGet publisher profile
Packages (154)
FSharp.Data
The FSharp.Data packages contain type providers and utilities to access common data formats (CSV, HTML, JSON and XML in your F# applications and scripts. * FSharp.Data -- includes everything * FSharp.Data.Http -- http types/helpers * FSharp.Data.Csv.Core -- csv types/helpers * FSharp.Data.Json.Core -- json types/helpers * FSharp.Data.Html.Core -- html types/helpers * FSharp.Data.Xml.Core -- xml types/helpers
FSharp.Control.AsyncSeq
Asynchronous sequences for F#
Deedle
Package Description
FSharp.Data.Http
The FSharp.Data packages contain type providers and utilities to access common data formats (CSV, HTML, JSON and XML in your F# applications and scripts. * FSharp.Data -- includes everything * FSharp.Data.Http -- http types/helpers * FSharp.Data.Csv.Core -- csv types/helpers * FSharp.Data.Json.Core -- json types/helpers * FSharp.Data.Html.Core -- html types/helpers * FSharp.Data.Xml.Core -- xml types/helpers
FSharp.Data.Json.Core
The FSharp.Data packages contain type providers and utilities to access common data formats (CSV, HTML, JSON and XML in your F# applications and scripts. * FSharp.Data -- includes everything * FSharp.Data.Http -- http types/helpers * FSharp.Data.Csv.Core -- csv types/helpers * FSharp.Data.Json.Core -- json types/helpers * FSharp.Data.Html.Core -- html types/helpers * FSharp.Data.Xml.Core -- xml types/helpers
FSharp.Data.Csv.Core
The FSharp.Data packages contain type providers and utilities to access common data formats (CSV, HTML, JSON and XML in your F# applications and scripts. * FSharp.Data -- includes everything * FSharp.Data.Http -- http types/helpers * FSharp.Data.Csv.Core -- csv types/helpers * FSharp.Data.Json.Core -- json types/helpers * FSharp.Data.Html.Core -- html types/helpers * FSharp.Data.Xml.Core -- xml types/helpers
FSharp.Data.Xml.Core
The FSharp.Data packages contain type providers and utilities to access common data formats (CSV, HTML, JSON and XML in your F# applications and scripts. * FSharp.Data -- includes everything * FSharp.Data.Http -- http types/helpers * FSharp.Data.Csv.Core -- csv types/helpers * FSharp.Data.Json.Core -- json types/helpers * FSharp.Data.Html.Core -- html types/helpers * FSharp.Data.Xml.Core -- xml types/helpers
FSharp.Data.WorldBank.Core
The FSharp.Data packages contain type providers and utilities to access common data formats (CSV, HTML, JSON and XML in your F# applications and scripts. * FSharp.Data -- includes everything * FSharp.Data.Http -- http types/helpers * FSharp.Data.Csv.Core -- csv types/helpers * FSharp.Data.Json.Core -- json types/helpers * FSharp.Data.Html.Core -- html types/helpers * FSharp.Data.Xml.Core -- xml types/helpers
FSharp.Data.Adaptive
FSharp.Data.Adaptive provides an incremental evaluation system inspired by Adapton, DeltaML and many others for FSharp. The implementation provides incremental datastructures for refs/sets/lists/maps.
TorchSharp
.NET Bindings for Torch. Requires reference to one of libtorch-cpu, libtorch-cuda-12.8, libtorch-cuda-12.8-win-x64 or libtorch-cuda-12.8-linux-x64 version 2.10.0.0 to execute.
FSharp.Compiler.Tools
FSharp.Compiler.Tools for F# 4.5 FSharp.Compiler.Tools built by F# Software Foundation This package includes the F# compiler (fsc.exe), F# Interactive (fsi.exe, fsiAnyCpu.exe) and the MSBuild component (FSharp.Build.dll). NOTE: the compiler executes with .NET Framework and/or Mono. It does not execute with .NET Core. For a compiler that executes with .NET Core use the .NET Core SDK, which includes an F# compiler.
FSharp.Formatting
The package is a collection of libraries that can be used for literate programming with F# (great for building documentation) and for generating library documentation from inline code comments. The key components are Markdown parser, tools for formatting F# code snippets, including tool tip type information and a tool for generating documentation from library metadata.
libtorch-cpu-linux-x64
TorchSharp makes PyTorch available for .NET users. libtorch-cpu-linux-x64 contains components of the PyTorch LibTorch library version 2.10.0 redistributed as a NuGet package with added support for TorchSharp.
FSharp.Formatting.CommandTool
The package is a collection of libraries that can be used for literate programming with F# (great for building documentation) and for generating library documentation from inline code comments. The key components are Markdown parser, tools for formatting F# code snippets, including tool tip type information and a tool for generating documentation from library metadata.
libtorch-cpu-win-x64
TorchSharp makes PyTorch available for .NET users. libtorch-cpu-win-x64 contains components of the PyTorch LibTorch library version 2.10.0 redistributed as a NuGet package with added support for TorchSharp.
TorchSharp-cuda-windows
TorchSharp makes PyTorch available for .NET users. This package combines the TorchSharp package with LibTorch 2.10.0 CUDA 12.8 support for Windows.
MBrace.Core
The MBrace core library contains all cloud computation essentials, libraries and local execution tools for authoring distributed code.
fsdocs-tool
The 'dotnet fsdocs' documentation generation tool for F# projects. Install use 'dotnet tool add fsdocs-tool'. See the project site for documentation.
libtorch-cpu-osx-x64
TorchSharp makes PyTorch available for .NET users. libtorch-cpu-osx-x64 contains components of the PyTorch LibTorch library version 2.2.1 redistributed as a NuGet package with added support for TorchSharp.
FSharp.Charting
The F# Charting library (FSharp.Charting.dll) is a compositional library for creating charts from F# on Windows. Use FSharp.Charting.Gtk for other platforms. FSharp.Charting is designed to be a great fit for data scripting in F# Interactive, but charts can also be embedded in Windows applications. The library is a wrapper for .NET Chart Controls, which are only supported on Windows.
DiffSharp.Core
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/
MBrace.Runtime
MBrace runtime core library containing the foundations for implementing distributed runtimes that support cloud workflows. The runtime core uses FsPickler and Vagabond as a foundation for communication and upload of code.
libtorch-cpu
TorchSharp makes PyTorch available for .NET users. libtorch-cpu contains components of the PyTorch LibTorch library version 2.10.0 redistributed as a NuGet package with added support for TorchSharp.
FsLab
FsLab is a combination package that supports doing data science with F#. FsLab includes literate scripting converted to HTML and PDF, and by default references Deedle (a data frame library), FSharp.Data (for data access) and XPlot (for visualization). You can optionally add any other nuget packages.
TorchSharp-cpu
TorchSharp makes PyTorch available for .NET users. This package combines the TorchSharp package with LibTorch 2.10.0 CPU support.
FSharp.Stats
F#-first linear algebra, machine learning, fitting, signal processing, and statistical testing.
XPlot.GoogleCharts
XPlot is a cross-platform data visualization library that supports creating charts using Google Charts and Plotly. The library provides a composable domain specific language for building charts and specifying their properties.
RProvider
An F# Type Provider providing strongly typed access to the R statistical language. The type provider automatically discovers available R packages and makes them easily accessible from F#, so you can easily call powerful packages and visualization libraries from code running on the .NET platform.
MBrace.Azure
MBrace on Windows Azure.
DiffSharp.Backends.Torch
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/
libtorch-cuda-11.3-win-x64-part11
(see main package)
libtorch-cuda-11.3-win-x64-part1
(see main package)
TorchSharp-cuda-linux
TorchSharp makes PyTorch available for .NET users. This package combines the TorchSharp package with LibTorch 2.10.0 CUDA 12.8 support for Linux.
libtorch-cuda-11.3-win-x64-part2
(see main package)
FSharp.Compiler.CodeDom
A limited CodeDom implementation for F#
MBrace.Flow
MBrace library for distributing flow computations.
DiffSharp.Backends.Reference
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/
libtorch-cuda-11.3-win-x64-part8
(see main package)
Deedle.RPlugin
Deedle implements an efficient and robust frame and series data structures for manipulating with structured data. It supports handling of missing values, aggregations, grouping, joining, statistical functions and more. For frames and series with ordered indices (such as time series), automatic alignment is also available. This package installs core Deedle package, together with an R type provider plugin which makes it possible to pass data frames and time series between R and Deedle
libtorch-cuda-11.3-win-x64-part3-fragment1
(see main package)
libtorch-cuda-11.3-win-x64-part9-fragment1
(see main package)
libtorch-cuda-11.3-win-x64-part9-fragment2
(see main package)
libtorch-cuda-11.3-win-x64-part5
(see main package)
libtorch-cuda-11.3-win-x64-part4
(see main package)
libtorch-cuda-11.3-win-x64-part10
(see main package)
libtorch-cuda-11.3-win-x64-part3-fragment2
(see main package)
libtorch-cuda-11.3-win-x64-part6
(see main package)
libtorch-cuda-11.1-win-x64-part11
(see main package)
FSharp.Compiler.Service.ProjectCracker
Legacy project file cracker for the F# compiler service.
MBrace.Tests
A collection of abstract NUnit-based test suites for evaluating MBrace runtime implementations.
libtorch-cuda-11.3-win-x64-part9-primary
(see main package)
libtorch-cuda-11.1-win-x64-part1
(see main package)
libtorch-cuda-11.3-win-x64-part9-fragment3
(see main package)
DiffSharp-cuda-windows
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/
MBrace.Thespian
Provides a simple MBrace cluster implementation over Nessos.Thespian.
libtorch-cuda-11.3-win-x64-part3-primary
(see main package)
libtorch-cuda-11.1-win-x64-part2
(see main package)
XPlot.GoogleCharts.Deedle
XPlot is a cross-platform data visualization library that supports creating charts using Google Charts and Plotly. The library provides a composable domain specific language for building charts and specifying their properties.
libtorch-cuda-11.3-win-x64-part7
(see main package)
libtorch-cuda-11.3-win-x64
TorchSharp makes PyTorch available for .NET users. libtorch-cuda-11.3-win-x64 contains components of the PyTorch LibTorch library version 1.11.0 redistributed as a NuGet package with added support for TorchSharp.
libtorch-cuda-11.1-win-x64-part3-fragment1
(see main package)
libtorch-cuda-11.1-win-x64-part10
(see main package)
DiffSharp-cuda-linux
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/
libtorch-cuda-11.1-linux-x64-part1
(see main package)
DiffSharp.Data
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/
libtorch-cuda-11.1-win-x64-part6
(see main package)
libtorch-cuda-11.1-linux-x64-part2-fragment4
(see main package)
libtorch-cuda-11.1-linux-x64-part2-fragment3
(see main package)
libtorch-cuda-11.1-win-x64-part3-fragment2
(see main package)
libtorch-cuda-11.1-linux-x64-part2-fragment5
(see main package)
libtorch-cuda-11.1-win-x64-part7-fragment1
(see main package)
libtorch-cuda-11.1-win-x64-part5
(see main package)
DiffSharp-cpu
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/
libtorch-cuda-11.1-linux-x64-part2-fragment6
(see main package)
DiffSharp-lite
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/
libtorch-cuda-11.1-linux-x64-part3-fragment1
(see main package)
libtorch-cuda-11.1-win-x64-part8
(see main package)
libtorch-cuda-11.1-linux-x64-part3-fragment3
(see main package)
libtorch-cuda-11.1-linux-x64-part3-fragment2
(see main package)
libtorch-cuda-11.1-win-x64-part9-fragment2
(see main package)
libtorch-cuda-11.1-win-x64-part9-fragment1
(see main package)
libtorch-cuda-11.1-win-x64-part7-fragment2
(see main package)
libtorch-cuda-11.1-win-x64-part9-fragment4
(see main package)
libtorch-cuda-11.1-win-x64-part9-fragment3
(see main package)
libtorch-cuda-11.1-linux-x64-part2-fragment7
(see main package)
FsLab.Runner
This package contains a library for turning FsLab experiments written as script files into HTML and LaTeX reports. The easiest way to use the library is to use the 'FsLab Journal' Visual Studio template.
MBrace.Azure.Management
MBrace.Azure cluster management library.
libtorch-cuda-11.1-linux-x64-part3-primary
(see main package)
FSharp.Compiler.Service.MSBuild.v12
Additional DLL for legacy compat for the F# compiler service.
libtorch-cuda-11.1-win-x64-part9-primary
(see main package)
libtorch-cuda-11.1-win-x64-part9-fragment5
(see main package)
libtorch-cuda-11.1-win-x64-part4
(see main package)
libtorch-cuda-11.1-win-x64-part7-primary
(see main package)
libtorch-cuda-11.3-linux-x64-part1
(see main package)
libtorch-cuda-11.3-linux-x64-part2-fragment2
(see main package)
libtorch-cuda-11.3-linux-x64-part2-fragment3
(see main package)
libtorch-cuda-11.1-win-x64
TorchSharp makes PyTorch available for .NET users. libtorch-cuda-11.1-win-x64 contains components of the PyTorch LibTorch library version 1.9.0 redistributed as a NuGet package with added support for TorchSharp.
libtorch-cuda-11.1-win-x64-part3-primary
(see main package)
libtorch-cuda-11.1-linux-x64-part2-fragment2
(see main package)
libtorch-cuda-11.3-linux-x64-part2-fragment4
(see main package)
libtorch-cuda-11.1-linux-x64-part2-fragment1
(see main package)
libtorch-cuda-11.3-linux-x64-part2-fragment5
(see main package)
libtorch-cuda-11.3-linux-x64-part3-fragment1
(see main package)
libtorch-cuda-11.3-linux-x64-part3-fragment2
(see main package)
libtorch-cuda-11.1-linux-x64-part2-primary
(see main package)
libtorch-cuda-11.3-linux-x64-part2-fragment6
(see main package)
libtorch-cuda-11.3-linux-x64-part3-primary
(see main package)
libtorch-cuda-11.3-linux-x64-part3-fragment3
(see main package)
FSharp.Formatting.Literate
The package is a collection of libraries that can be used for literate programming with F# (great for building documentation) and for generating library documentation from inline code comments. The key components are Markdown parser, tools for formatting F# code snippets, including tool tip type information and a tool for generating documentation from library metadata.
libtorch-cuda-11.3-linux-x64-part2-fragment1
(see main package)
libtorch-cuda-11.1-linux-x64-part4
(see main package)
libtorch-cuda-11.1-linux-x64-part3-fragment4
(see main package)
libtorch-cuda-11.1-linux-x64
TorchSharp makes PyTorch available for .NET users. libtorch-cuda-11.1-linux-x64 contains components of the PyTorch LibTorch library version 1.9.0 redistributed as a NuGet package with added support for TorchSharp.
libtorch-cuda-11.1-linux-x64-part2-fragment8
(see main package)
libtorch-cuda-11.3-linux-x64-part2-primary
(see main package)
libtorch-cuda-11.3-win-x64-part9-fragment4
(see main package)
DiffSharp
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 truncation and round-off errors, and symbolic differentiation, which is affected by expression swell and cannot fully handle algorithmic control flow. Using the DiffSharp library, derivative calculations (gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products) can be incorporated with minimal change into existing algorithms. Diffsharp supports nested forward and reverse AD up to any level, meaning that you can compute exact higher-order derivatives or differentiate functions that are internally making use of differentiation. Please see the API Overview page for a list of available operations. The library is under active development by Atılım Güneş Baydin and Barak A. Pearlmutter mainly for research applications in machine learning, as part of their work at the Brain and Computation Lab, Hamilton Institute, National University of Ireland Maynooth. DiffSharp is implemented in the F# language and can be used from C# and the other languages running on .NET Core, Mono, or the .NET Framework; targeting the 64 bit platform. It is tested on Linux and Windows. We are working on interfaces/ports to other languages.
libtorch-cuda-11.3-linux-x64
TorchSharp makes PyTorch available for .NET users. libtorch-cuda-11.3-linux-x64 contains components of the PyTorch LibTorch library version 1.11.0 redistributed as a NuGet package with added support for TorchSharp.
FSharp.Core.Fluent-4.0
Fluent extensions for FSharp.Core
libtorch-cuda-11.1-linux-x64-part2-fragment10
(see main package)
libtorch-cuda-11.3-linux-x64-part2-fragment7
(see main package)
Thespian
A declarative command line and XML configuration parser for F# applications.
libtorch-cuda-11.1-linux-x64-part2-fragment9
(see main package)
libtorch-cuda-11.3-linux-x64-part4
(see main package)
MBrace.CSharp
MBrace wrappers and utilities for C#
FSharp.Literate
The package is a collection of libraries that can be used for literate programming with F# (great for building documentation) and for generating library documentation from inline code comments. The key componments are Markdown parser, tools for formatting F# code snippets, including tool tip type information and a tool for generating documentation from library metadata.
libtorch-cuda-11.3-linux-x64-part3-fragment4
(see main package)
libtorch-cuda-10.2-win-x64-part2
(see main package)
FSharp.Charting.Gtk
The F# Charting Gtk library (FSharp.Charting.Gtk.dll) is a cross-platform variation of of FSharp.Charting. It can be used on Windows, OSX and other platforms supporting Gtk. See also th https://fslab.org/XPlot library for cross-platform charting.
MBrace.Runtime.Core
MBrace runtime core library containing the foundations for implementing distributed runtimes that support cloud workflows.
libtorch-cuda-10.2-win-x64-part4-primary
(see main package)
libtorch-cuda-10.2-win-x64-part4-fragment1
(see main package)
Deedle.Excel
Package Description
FSharp.TypeProviders.Templates
`dotnet new` template for building F# Type Providers.
XPlot.GoogleCharts.WPF
XPlot is a cross-platform data visualization library that supports creating charts using Google Charts and Plotly. The library provides a composable domain specific language for building charts and specifying their properties.
libtorch-cuda-10.2-win-x64-part3
(see main package)
DiffSharp-cuda
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/
XPlot.Plotly.WPF
XPlot is a cross-platform data visualization library that supports creating charts using Google Charts and Plotly. The library provides a composable domain specific language for building charts and specifying their properties.
FSharp.Core.Fluent-3.1
Fluent members for Seq, List, Array and all F# 3.1 FSharp.Core functions
libtorch-cuda-10.2-win-x64-part5
(see main package)
FSharp.Data.Experimental.XenomorphProvider
The FSharp.Data.Experimental.XenomorphProvider type provider provides a strongly typed embedding of financial data from Xenomorph.TimeScape
Hype
Hype is a proof-of-concept deep learning library, where you can perform optimization on compositional machine learning systems of many components, even when such components themselves internally perform optimization. This is enabled by nested automatic differentiation (AD) giving you access to the automatic exact derivative of any floating-point value in your code with respect to any other. Underlying computations are run by a BLAS/LAPACK backend (OpenBLAS by default).
libtorch-cuda-10.2-win-x64-part4-fragment2
(see main package)
FSharp.Core.Fluent
Fluent extensions for FSharp.Core
FSharp.Formatting.Razor
The package is a collection of libraries that can be used for literate programming with F# (great for building documentation) and for generating library documentation from inline code comments. The key componments are Markdown parser, tools for formatting F# code snippets, including tool tip type information and a tool for generating documentation from library metadata.
FSharp.Data.DbPedia
An F# type provider for DBpedia, allowing you to browse and query Wikipedia knowledge in a strongly typed way
AtenSharp
.NET Bindings for Torch
libtorch-cuda-11.3-linux-x64-part2-fragment10
(see main package)
FsMath
FsMath is a lightweight maths library designed for modern F# workflows. It focuses on zero-friction interop with existing array-centric libraries ( FSharp.Stats, Math.NET Numerics, libtorch via TorchSharp, etc.) while giving you the performance head-room of SIMD-accelerated kernels and a clean, idiomatic F# API.
Fable.React.Adaptive
Fable.React.Adaptive provides react bindings for adaptive values from FSharp.Data.Adaptive.
libtorch-cuda-11.3-linux-x64-part2-fragment8
(see main package)
libtorch-cuda-11.3-linux-x64-part2-fragment9
(see main package)
Fable.Elmish.Adaptive
Fable.Elmish.Adaptive provides an elmish(ish) frontend for writing web apps with FSharp.Data.Adaptive
DiffSharp.IO
Package Description