What is Backpropagation?

📌 AI Interview Question #19: What is Backpropagation?

🔄 Backpropagation is the process used to train neural networks by adjusting weights to minimize the error between the predicted and actual output.

How It Works:

1. Forward Pass: Input data is passed through the network to generate a prediction.
2. Calculate Error: The error (difference between predicted output and actual output) is calculated.
3. Backward Pass: This error is propagated backward through the network to update the weights and biases, typically using the gradient descent algorithm.
4. Update Weights: The weights are adjusted to minimize the error for better predictions in future iterations.
Key Takeaway:

Backpropagation allows neural networks to "learn" from the errors and improve accuracy with each iteration.

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Видео What is Backpropagation? канала Sharmistha Majumder
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