What is regularization in machine learning? Regularization in machine learning is a set of techniques used to ensure that a machine learning model can generalize to new data within the same data set.

A new survey in Machine Learning rebuilds the theory of regularization from ill-posed problems up and maps the modern ...

Regularization changes the training objective, architecture, or stopping process to discourage brittle complexity and improve ...

Our data science expert continues his exploration of neural network programming, explaining how regularization addresses the problem of model overfitting, caused by network overtraining. Neural ...