SciSharp STACK alternatives and similar packages

Based on the "Machine Learning and Data Science" category.

ML.NET

9.6 0.0 SciSharp STACK VS ML.NET

ML.NET is an open source and cross-platform machine learning framework for .NET.
Accord.NET

9.5 6.7 L2 SciSharp STACK VS Accord.NET

Machine learning framework combined with audio and image processing libraries (computer vision, computer audition, signal processing and statistics).

Collect and Analyze Billions of Data Points in Real Time

Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.

Promo www.influxdata.com

TensorFlow.NET

8.4 0.0 SciSharp STACK VS TensorFlow.NET

.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.
m2cgen

7.7 0.0 SciSharp STACK VS 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

7.1 0.0 L2 SciSharp STACK VS 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.
F# Data

6.3 0.0 SciSharp STACK VS F# Data

F# Data: Library for Data Access
Deedle

6.3 0.0 SciSharp STACK VS Deedle

Easy to use .NET library for data and time series manipulation and for scientific programming
Accord.NET Extensions

6.1 0.0 L5 SciSharp STACK VS Accord.NET Extensions

Advanced image processing and computer vision algorithms made as fluent extensions.
encog-dotnet-core

5.5 0.0 SciSharp STACK VS encog-dotnet-core

Encog Machine Learning Framework
numl

5.2 0.0 L3 SciSharp STACK VS numl

Machine Learning for .NET
Catalyst

5.1 0.0 SciSharp STACK VS 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.
Spreads

4.6 0.0 SciSharp STACK VS Spreads

Series and Panels for Real-time and Exploratory Analysis of Data Streams
R Provider

4.3 0.0 SciSharp STACK VS R Provider

Access R packages from F#
Synapses

2.3 0.0 SciSharp STACK VS Synapses

A group of neural-network libraries for functional and mainstream languages
Infer.NET

1.9 0.0 SciSharp STACK VS Infer.NET

UAI 2015. Kernel-based just-in-time learning for expectation propagation
FsLab

1.4 0.0 SciSharp STACK VS FsLab

FsLab project templates - download as ZIP to get started!