9 open-source projects similar to fsprojects/fsharp.data, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best FSharp.Data alternative.
This project is a scientific computing framework for the .NET ecosystem, providing a comprehensive suite of libraries for numerical analysis, statistics, and mathematical optimization. It serves as a foundational toolkit for developing applications in machine learning, digital signal processing, and computer vision. The framework provides specialized toolkits for training and deploying predictive models, including neural networks, support vector machines, and decision trees. It further distinguishes itself with deep integrations for real-time visual analysis, such as object tracking and facia
An extensible .NET genetic algorithm library for optimization and artificial intelligence - Evolutionary computation and complex problem solving made simple
🚀 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.
This is a cross-platform framework for building, training, and deploying custom machine learning models within the .NET ecosystem. It provides a predictive modeling engine for classification, regression, and forecasting tasks, alongside an inference runtime to generate predictions across different hardware architectures. The framework includes a gradient boosting library and supports interoperability with external models via a standardized open format. It features tools for prediction explainability, allowing the analysis of feature importance to debug model behavior and identify bias. The p
GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs).
TensorFlow API for .NET languages
WaveFunctionCollapse is a procedural generation engine that creates complex, non-repeating patterns by treating spatial arrangement as a constraint satisfaction problem. It functions as a stochastic solver that derives output structures from a single input example, ensuring that every element placed within a grid satisfies specific adjacency requirements relative to its neighbors. The system distinguishes itself by using an entropy-driven approach to grid collapse, where it iteratively selects the cell with the fewest remaining possibilities to trigger a cascade of logical updates. By decompo
Series and Panels for Real-time and Exploratory Analysis of Data Streams