This repository applies various unsupervised learning methods to the MNIST dataset of handwritten digits. Techniques include k-Means, Hierarchical Clustering, DBSCAN, GMM, PCA, t-SNE, Autoencoders, Isolation Forest, One-Class SVM, LDA, SOM, Agglomerative Clustering, Mean Shift, and Spectral Clustering. Explore the code and visualizations here!
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This repository applies various unsupervised learning methods to the MNIST dataset of handwritten digits. Techniques include k-Means, Hierarchical Clustering, DBSCAN, GMM, PCA, t-SNE, Autoencoders, Isolation Forest, One-Class SVM, LDA, SOM, Agglomerative Clustering, Mean Shift, and Spectral Clustering. Explore the code and visualizations here!
Msoltaninezhad/unsupervised_learning_MNIST
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This repository applies various unsupervised learning methods to the MNIST dataset of handwritten digits. Techniques include k-Means, Hierarchical Clustering, DBSCAN, GMM, PCA, t-SNE, Autoencoders, Isolation Forest, One-Class SVM, LDA, SOM, Agglomerative Clustering, Mean Shift, and Spectral Clustering. Explore the code and visualizations here!
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