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Understand how neural networks learn by propagating errors backwards through layers, using the chain rule to update every weight.
By the end of this lesson, you will understand:
In the previous lessons you saw that neural networks have weights, and training adjusts those weights. But how does the network know which weights to change, and by how much? The answer is backpropagation - the single most important algorithm in modern deep learning. Andrej Karpathy calls it "the most important thing to understand about neural networks." Let us see why.
Backpropagation - The Calculus Behind Learning is part of AI Sprouts
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