# One-hot encoding

## Definition of One-hot encoding

One-hot encoding: One-hot encoding is a technique used in machine learning to represent categorical variables as a vector of binary values. In one-hot encoding, each category is represented by a unique integer value, and the remaining values are set to 0. For example, if there are three categories, A, B, and C, then the vector would be [0, 1, 0]. This encoding allows for easy determination of the category of a given value, as well as efficient storage and manipulation.