Professional Certificate in Spectral Clustering for Analysts
-- ViewingNowThe Professional Certificate in Spectral Clustering for Analysts is a comprehensive course designed to empower data analysts with advanced clustering techniques. This certificate course emphasizes the importance of spectral clustering, a powerful method for dividing complex data sets into meaningful groups.
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โข Introduction to Spectral Clustering: Fundamentals, concepts, and applications of spectral clustering. โข Data Preprocessing: Data cleaning, normalization, and transformation techniques. โข Graph Theory Basics: Key concepts of graph theory, including nodes, edges, and adjacency matrices. โข Similarity Measures: Distance metrics, kernel functions, and similarity measures. โข Spectral Decomposition: Eigendecomposition, eigenvalues, and eigenvectors. โข Clustering Algorithms: K-means, hierarchical clustering, and density-based clustering. โข Spectral Clustering Implementation: Building spectral clustering algorithms from scratch. โข Performance Evaluation: Internal and external validation metrics, clustering stability. โข Advanced Topics: Multiple graph construction methods, normalized cuts, and spectral clustering variations.
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