“Backpropagation Explained: The Math Behind Neural Networks” скачать в хорошем качестве

“Backpropagation Explained: The Math Behind Neural Networks”

Backpropagation is the algorithm that made deep learning possible. In this video, we break down the mathematics step by step — from the chain rule of calculus to gradient descent — and show how errors flow backward through a neural network to update its weights. You’ll learn: The intuition behind backpropagation How derivatives and the chain rule drive learning Why backpropagation is essential for training deep models Historical context and its impact on modern AI Whether you’re a student, researcher, or curious learner, this video will give you both the intuition and the equations that power today’s machine learning revolution. 👉 Subscribe to Maths Behind for more videos that uncover the mathematics at the heart of AI.