numl | F# Data | |
---|---|---|
- | 6 | |
429 | 805 | |
- | 0.6% | |
0.0 | 6.8 | |
over 5 years ago | 13 days ago | |
C# | F# | |
MIT License | GNU General Public License v3.0 or later |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
numl
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Tracking mentions began in Dec 2020.
F# Data
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A new Excel add-in for custom functions and much more using F#. A replacement for VBA?
It is a brilliant tool for being able to import and export data in almost any format from your local computer, a database or across the web. For common data formats like csv, xml, and json, the Type Providers in FSharp.Data allow you automatically generate a type safe API against a sample file.
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Why learn Racket? A student's perspective
F# has this kind of stuff also, where it will dynamically type data dynamic sources like databases or rest calls, etc. for an example https://fsprojects.github.io/FSharp.Data/
- Twenty Years of C# with Anders Hejlsberg [audio]
- FSharp.Data: Data Access Made Simple
- FSharp.Data 4.1.1 Released
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F# Async Webrequest?
Have a look at the FSharp.Data library. It has bunch of cool stuff including Http.
What are some alternatives?
Accord.NET
Deedle - Easy to use .NET library for data and time series manipulation and for scientific programming
Accord.NET Extensions
TensorFlow.NET - .NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.
Catalyst - 🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
R Provider - Access R packages from F#
encog-dotnet-core
AForge.NET - AForge.NET Framework is a C# framework designed for developers and researchers in the fields of Computer Vision and Artificial Intelligence - image processing, neural networks, genetic algorithms, machine learning, robotics, etc.
Infer.NET - UAI 2015. Kernel-based just-in-time learning for expectation propagation