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Principal Component Analysis (PCA) | by Shaw Talebi | Towards Data Science

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This is the first post in a two-part series on Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Although they have similarities (such as their names), they each achieve different tasks. In this post, I will describe what PCA is, how it works, and, as an example, use it to define an S&P 500 index fund. Example code and other related resources can be found in the last section of this post. Imagine a big rock band with about 20 members. It features guitarists, background singers, pianists, keyboardists, a horn section, drummers, percussionists, etc. A big band needs a big stage. This is not a problem for venues like Madison Square Garden or Wembley Stadium, but what if they are starting out and can only play coffee shops? Well, instead of 3 guitars, there could be one. Instead of 2 drummers and a percussionist, one could play the bongos. And instead of a piano, electric piano, and synthesizer on stage, one member could play a keyboard. You wouldn’t get the full

Principal Component Analysis (PCA) | Towards Data Science Data Science Principal Component Analysis (PCA) Intuition, math, and stonks Shaw Talebi Feb 22, 2021 9 min read Share This is the first post in a two-part series on Principal Component Analysis (PCA) and Independent Component Analysis (ICA) . Although they have similarities (such as their names), they each achieve different tasks. In this post, I will describe what PCA is, how it works, and, as an example, use it to define an S&P 500 index fund. Example code and other related resources can be found in the last section of this post. PCA

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