Chain rule Explained

What is the Chain Rule and how is it used in Neural Networks? In this video, we visually explain the **Chain Rule**, a fundamental concept from calculus that is essential for training neural networks in Artificial Intelligence and Deep Learning. The chain rule allows us to compute how changes in one variable affect another through a sequence of functions. In neural networks, this is crucial for calculating gradients across multiple layers, enabling the model to learn by adjusting its parameters. Through simple visual animations, this video demonstrates how the chain rule works step by step and how it powers the backpropagation algorithm used in training AI models. In this video you will learn: • What the chain rule is • How functions are composed in neural networks • How gradients flow through multiple layers • How the chain rule is used in backpropagation • Why the chain rule is essential for training deep learning models Understanding the chain rule is a key step in learning how neural networks learn from data and improve predictions. This channel explains AI concepts using clear visual explanations to make complex ideas simple and intuitive. Subscribe for more videos on: Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, and the mathematics behind AI. #artificialintelligence #machinelearning #deeplearning #chainrule #aiexplained #agenticai #generativeai