【ML】One hot encoding

What: In machine learning, one-hot encoding is a frequently used method to deal with categorical data. One-hot is a group of bits among which the legal combinations of values are only those wit a single high (1) bit and all the others low (0). (1 can mean TRUE, 0 can mean FALSE)

Why: Because many machine learning models need their input variables to be numeric, categorical variables need to be transformed in the pre-processing part.