“Backpropagation Explained: The Math Behind Neural Networks”
Автор: Maths Behind
Загружено: 2026-01-12
Просмотров: 8
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.
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