FsLab alternatives and similar packages
Based on the "Machine Learning and Data Science" category.
Alternatively, view FsLab alternatives based on common mentions on social networks and blogs.
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ML.NET
ML.NET is an open source and cross-platform machine learning framework for .NET. -
Accord.NET
Machine learning framework combined with audio and image processing libraries (computer vision, computer audition, signal processing and statistics). -
TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#. -
m2cgen
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies -
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. -
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Deedle
Easy to use .NET library for data and time series manipulation and for scientific programming -
Accord.NET Extensions
Advanced image processing and computer vision algorithms made as fluent extensions. -
Spreads
Series and Panels for Real-time and Exploratory Analysis of Data Streams -
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. -
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Synapses
A group of neural-network libraries for functional and mainstream languages -
Infer.NET
UAI 2015. Kernel-based just-in-time learning for expectation propagation -
SciSharp STACK
A rich machine learning ecosystem for .NET created by porting the most popular Python libraries to C#.
Less time debugging, more time building
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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Popular Comparisons
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FsLabvsAccord.NET
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README
FsLab project templates
This repository hosts FsLab project templates compatible with many F# editors. Using the templates, you can start with FsLab in 3 simple steps:
- Download a selected template
- Build it to download FsLab packages
- Open scripts in your editor & play!
1. Download a template
To get started, download a branch with the template as a ZIP file and extract the files. The repository currently hosts the following templates:
- FsLab Basic template - references FsLab and gives you a single script file with simple demo
- FsLab Journal template - in addition to the above, this template also lets you write literate FsLab scripts and produce HTML or LaTeX reports
2. Build the template
Visual Studio and Xamarin Studio should download FsLab packages automatically on build. If this doesn't happen (or when using other editors), you need to explicitly install them.
In the basic template, run
paket install. For example, when using mono on Mac, run:mono .paket/paket.bootstrapper.exe mono .paket/paket.exe installIn the journal template you can use build scripts
build.shandbuild.cmd. The following will process all journals and open them in a web browser:chmod +x build.sh ./build.sh run
3. Use FsLab for fun & profit!
Once you have the template and packages, you can open the Tutorial.fsx file and start playing
with FsLab. For more information, see the Getting Started page on www.fslab.org.