Momentum – part 3 – day 35
Comprehensive Guide: Understanding Gradient Descent and Momentum in Deep Learning Gradient descent is a cornerstone algorithm in the field of deep learning, serving as the primary method by which neural networks optimize their weights to minimize the loss function. This article will delve into the principles of gradient descent, its importance in deep learning, how momentum enhances its performance, and the role it plays in model training. We will also explore practical examples to illustrate these concepts. What is Gradient Descent? Gradient Descent is an optimization algorithm used to minimize a loss function by iteratively adjusting the model’s parameters (weights...
