Regularization

Regularization is a machine learning technique used to prevent model overfitting by adding a penalty term to the loss function, thereby improving the model's ability to generalize to new, unseen data. By reducing overfitting, regularization helps developers create more robust and reliable AI models that perform well in real-world applications, making it a crucial aspect of model development and deployment in the tech industry.