Dimensionality Reduction and Principal Component Analysis

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Dimensionality Reduction and Principal Component Analysis[ Edit ]

Dimensionality reduction aims to reduce the number of features of a high dimensional dataset in order to overcome the difficulties that arise due to the curse of dimensionality.

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Category: Machine Learning

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The Curse of Dimensionality

End-to-End Example: Using Logistic Regression for predicting Diabetes

About the contributors

Marta EnescoData Scientist, Graduate Research Assistant at University of Potsdam

Anant JainCo-Founder, CommonLounge

Keshav DhandhaniaMachine Learning @ MIT (2014). DM me for 1-on-1 mentorship (paid).

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