Label and One-Hot Encoding #ai #machinelearning #datascience #datacleaning #preprocessing

In this short video, we break down how machine learning models handle text by converting it into numbers through a process called encoding. When a dataset has words like city names or letter grades, models can’t understand them directly, so we use techniques like label encoding and one-hot encoding to translate text into numerical form. Label encoding assigns numbers to categories, which works when the order matters, like with letter grades, but can cause issues for unordered data such as cities. One-hot encoding solves that by creating separate columns and marking each with 0s and 1s, allowing models to learn without assuming any category is “greater” than another. This quick explanation shows why encoding is a crucial step in data cleaning for machine learning! #ai #machinelearning #datascience #datacleaning #preprocessing #mltips #deeplearning #techshorts #dataengineer #analytics #datasets #datatips #techlearning