self-organizing-maps

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michelin / TorchSOM

TorchSOM is a PyTorch-based library for training Self-Organizing Maps (SOMs), a type of unsupervised learning algorithm used for clustering and dimensionality reduction. Designed for scalability and ease of use, this implementation is optimized for large-scale data.

clustering pytorch data-visualisation clustering-algorithm unsupervised-machine-learning pytorch-implementation just-in-time self-organizing-maps dimensionality-reduction-technique dimensionality-reduction-algorithms just-in-time-learning

Updated Sep 2, 2025
Python

Ahmadhammam03 / credit-card-fraud-detection-som

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🔍 Advanced fraud detection system using Self-Organizing Maps for anomaly detection and Neural Networks for classification

python data-science machine-learning tensorflow neural-networks supervised-learning unsupervised-learning fraud-detection anomaly-detection self-organizing-maps

Updated Jul 19, 2025
Jupyter Notebook

rustic-ml / FormicaX

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FormicaX: Rust library with clustering algorithms like K-Means, DBSCAN, and GMM, FormicaX delivers efficient, adaptable insights for trading applications. Inspired by the collaborative and resilient nature of ants (Formica), it offers a modular, high-performance framework for developers and data scientists.

som gaussian-mixture-models gmm dbscan hierarchical-clustering affinity-propagation k-means-clustering self-organizing-maps