The power of Regularization in Machine learning

Regularization is not just a trick to reduce overfitting — it’s a deep mathematical principle that shapes how models generalize, how optimization behaves, and how learning algorithms balance complexity and stability. In this advanced episode of Maths Behind, we dissect regularization from first principles, exploring its role in statistical learning theory, optimization geometry, and modern deep learning practice.