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This assignment focuses on unsupervised learning techniques. The notebook explores clustering algorithms like K-Means and DBSCAN, applies dimensionality reduction using PCA, and evaluates clustering performance. It includes visualizations and analysis to understand how different methods group data and reduce complexity.

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train.csv		train.csv

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This assignment focuses on unsupervised learning techniques. The notebook explores clustering algorithms like K-Means and DBSCAN, applies dimensionality reduction using PCA, and evaluates clustering performance. It includes visualizations and analysis to understand how different methods group data and reduce complexity.

python pca-analysis dimensionality-reduction unsupervised-learning clustering-algorithm dbscan-clustering k-means-clustering

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