A Gentle Introduction to Data Augmentation

Too Long; Didn't Read

Data augmentation is a set of techniques used to increase the amount of data in a machine learning model by adding slightly modified copies of already existing data or newly created synthetic data from existing data. It helps smooth out the machine learning model and reduce the overfitting of data.  Businesses can use data augmentation to lessen their reliance on training data preparation and develop more accurate machine learning models faster. Data augmentation can also help machine learning models with lots of data already by increasing the amount of relevant data in the dataset.