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Abdesselam Benameur

Abdesselam Benameur

France •
1 post •
Machine Learning (ML)

Non-negative matrix factorization (NMF) vs Principal Component Analysis (PCA)

In the field of data analysis and dimensionality reduction, Non-negative Matrix Factorization (NMF) and Principal Component Analysis (PCA) are two powerful techniques that play an important role in uncovering patterns, reducing noise, and extracting essential features from complex datasets.

Abdesselam Benameur Abdesselam Benameur
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