Understanding-PCA
sharmaroshan
Principal Component Analysis is One of the Most Popular Dimensionality Reduction Algorithms used in Machine Learning Which comes under Unsupervised Way of Learning. It is also Used as a way of Feature Extraction where, More Information is Extracted from all the Existing Attributes, in just some 3-4 Attributes using the Concepts of Eigen Values and Eigen Vectors.
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3 data points · 2021-08-06 → 2022-02-01How do you feel about this project?
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Question copied to clipboardWhat is the sharmaroshan/Understanding-PCA GitHub project? Description: "Principal Component Analysis is One of the Most Popular Dimensionality Reduction Algorithms used in Machine Learning Which comes under Unsupervised Way of Learning. It is also Used as a way of Feature Extraction where, More Information is Extracted from all the Existing Attributes, in just some 3-4 Attributes using the Concepts of Eigen Values and Eigen Vectors.". Written in HTML. Explain what it does, its main use cases, key features, and who would benefit from using it.
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