regularization techniques2 Common regularization techniques in ML - Data augmentation Data augmentation is a technique used in machine learning and computer vision to artificially increase the size and diversity of the training dataset by applying a set of transformations to the existing data. The main goal of data augmentation is to introduce variations in the training data so that the model can learn and generalize better. By generating additional examples, data augmentation he.. 2023. 8. 2. Common regularization techniques in machine learning - Early Stopping Early stopping is a technique employed in machine learning to prevent overfitting of a model. It involves monitoring the performance of the model on a separate validation set during the training process. The validation set consists of data that the model has not been trained on and therefore provides a measure of how well the model generalizes to unseen data. The training process typically invol.. 2023. 8. 2. 이전 1 다음