I am learning about standardization and normalization concepts for feature engineering.
Standardization is done for example using z-score where based on the mean and std deviation we re-calculate the values so that the mean is 0 and std deviation is 1. This is a column wise operation.
Where as Normalization is performed row wise (to make the entire row unit norm) – thus making it good for calculating things like cosine similarity. I am looking for an example of what it means to make the row unit norm.