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Machine Learning Intermediate Pro

Clustering & Dimensionality Reduction

Find structure in unlabelled data with k-means, DBSCAN, GMMs, PCA, t-SNE and UMAP — and know when each one lies to you

28 min read 9 views

Learn k-means, hierarchical clustering, DBSCAN and Gaussian mixtures, how to choose k and evaluate clusters without labels, and how PCA, t-SNE and UMAP compress high-dimensional data — with a worked PCA example and interview traps.

Practice questions (5)

  • k-means Local Minimum by Hand

    Intermediate · Free
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  • Computing and Interpreting Silhouette Scores

    Intermediate
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  • Choosing Between k-means, DBSCAN and GMM

    Intermediate
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  • PCA on a Small Dataset

    Intermediate
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  • Misreading a t-SNE Plot

    Intermediate
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