Nowadays, we can vectorize everything such as numbers, words, sentences, etc. Why do we need to vectorize everything? We want to make everything countable and measurable so that we can apply many complicated statistical algorithms for it. That is why vectorization is one of the most important things in feature engineering. However, we do not discuss further those concepts in this notebook. Instead of that, this notebook shows how we calculate the distance between two vectors/observations by using different distance techniques.
It is clear that different normalization will be used for different purposes with different datasets. It is possible to use only one normalization technique for a particular dataset. Also, it is possible to use mixed normalization techniques (more than 2) for a different dataset. This notebook shows how we deal with the numeric data with different scale by using normalization techniques.