Explain weight initialization methods and goals

Q: Explain weight initialization methods and goals

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Question

Explain why weight initialization matters in deep neural networks.

Then describe common initialization methods (such as random normal/uniform, Xavier/Glorot, and He initialization):

How each method chooses the initial weight distribution.
What problem(s) they are designed to solve (e.g., vanishing/exploding activations or gradients, symmetry breaking).
When you would choose each method based on the activation functions used.

Explain weight initialization methods and goals

Solution

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