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