Mastering Categorical Encoding: One-Hot, Label, Target, and K-Fold Explained 📊

In theory, discrete variables, or features, are easy to use with machine learning algorithms. However, in practice, it's not always so easy and we often have to transform discrete values, like favorite colors, into numbers. There are lots of ways to do this, and this video walks you through 3 of the most popular methods.

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0:00 Awesome song and introduction
1:24 One-Hot Encoding
3:25 Label Encoding
4:39 Target Encoding
6:27 Target Encoding with a Weighted Mean, or Bayesian Target Encoding
9:56 K-Fold Target Encoding

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