#018 PyTorch - Popular techniques to prevent the Overfitting in a Neural Networks

In today's post, we will discuss one of the most common problems that arise during the training of deep neural networks. It is called overfitting, and it usually occurs when we increase the complexity of the network. In this post, you will learn the most common techniques to reduce overfitting while training neural networks. When building a neural network our goal is to develop a model that performs well on the training dataset, but also on the new data that it wasn't trained on. However, when our model is too complex, sometimes it can start to learn the irrelevant information in the dataset. That means that model memorizes the noise that is closely related only to the training dataset.