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Published 20 hours ago • verified publisher icon lucko515
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Metadata

Here I've demonstrated how and why should we use PCA, KernelPCA, LDA and t-SNE for dimensionality reduction when we work with higher dimensional datasets.

Dimensionality reduction using Python

In this repository you will find 3 different use cases of dimensionality reduction algorithms in practice.

Note: In the folder algorithms_numpy you will find custom implementation of PCA algorithm using only numpy.

More datails

Each project has its own README where you will find more information about a project itself.

License

Each project has MIT license

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verified publisher icon lucko515

Metadata

Here I've demonstrated how and why should we use PCA, KernelPCA, LDA and t-SNE for dimensionality reduction when we work with higher dimensional datasets.

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