Principal Component Analysis - Part 2
This is the second post of the series about Principal Component Analysis (PCA). Whilst the first post provided a theoretical background, this post will discuss the actual implementation of the PCA algorithm and its results when applied to some example data.
Theory Recap In the first post we learnt that PCA looks for a vector basis that can express the analysed data in a better (less redundant) way, whilst retaining as much information from the original data as possible.
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