In machine learning, the processes of training deep neural networks often encounter two critical challenges: exploding gradients and vanishing gradients. These issues can hinder the learning process, leading to inefficient or unstable model training. This discussion explores the causes of exploding and vanishing gradients, how they are measured, strategies to counteract them, and the role … Continue reading Exploding and Vanishing Gradients in Machine Learning: Causes, Solutions, and the Role of Optimization