In the realm of machine learning, training accurate and robust models is a constant pursuit. However, two common challenges that often hinder model performance are overfitting and underfitting. These ...

When considering overfitting, which is widely seen in the field of machine learning, it is important to say that ``an AI created for a specific goal cannot be trained with the goal itself, so a 'proxy ...

A new advancement in federated learning promises improved AI performance for sensitive sectors like healthcare and finance, ...

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...