How can you use dropout and weight decay to optimize deep learning models?
Deep learning models can achieve impressive results on complex tasks, but they also face some challenges, such as overfitting, underfitting, and high computational costs. To overcome these issues, you can use two common regularization techniques: dropout and weight decay. In this article, you will learn what dropout and weight decay are, how they work, and how to implement them in your deep learning models.