Unsupervised Learning
Showing 16 of 52 projects
An implementation of unsupervised image-to-image translation using Generative Adversarial Networks (GANs).
Interactive visual pattern search and exploration tool for epigenomic data using unsupervised deep representation learning.
A pattern recognition library for Go providing classification, clustering, and feature extraction algorithms.
A TensorFlow library implementing Restricted Boltzmann Machines and their variants for machine learning applications.
A simple JavaScript implementation of the k-means clustering algorithm for both Node.js and browser environments.
A Go implementation of k-modes and k-prototypes clustering algorithms for categorical and mixed data.
A Python implementation of the Optimum-Path Forest classifier for machine learning tasks.
An R package implementing Restricted Boltzmann Machines for collaborative filtering and feature learning.
JavaScript implementation of multivariate Gaussian mixture model for unsupervised clustering of offline and real-time data streams.
An open-source JavaScript library implementing machine learning algorithms for educational purposes with interactive visualizations.
A comprehensive Ruby gem providing atomic, flexible tools and frameworks for practical machine learning applications.
A comprehensive Ruby gem providing a collection of atomic machine learning tools and frameworks for practical applications.
A Haskell implementation of Hopfield networks for unsupervised learning and pattern storage.
An iOS implementation of the Hebbian algorithm for unsupervised self-organizing machine learning.
Implementation of the Partitioning Around Medoids (PAM) clustering algorithm within the H2O-3 machine learning platform.
An H2O-3 implementation of the Gap Statistic method for determining the optimal number of clusters in a dataset.
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