In this lesson, we dive deep into the mathematical core of neural network training. Backpropagation is the primary mechanism by which networks learn from errors. We will cover the chain rule application and weight optimization.
"I noticed you've been reviewing the partial derivatives section. Would you like a simplified visualization of how the gradient flows back through the layers?"