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What is DLT 3 about?

Backpropagation is a supervised learning algorithm essential for training neural networks, computing gradients of the loss function to optimize weights. It involves a forward pass to generate outputs, loss calculation, and a backward pass to adjust weights using gradient descent. Gradient descent, the primary optimization method, can face challenges such as local minima, saddle points, and vanishing or exploding gradients, which can hinder model performance.

Author

Palanivel Bit

Language

EN