Learning Path
Question & Answer
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Learning rate
Weight initialization
Activation function derivatives
Batch size
Understanding the Answer
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The derivative of an activation function tells how much the output changes when the input changes. Other options are incorrect because Learning rate controls how big a step we take when updating weights, not how the gradient itself behaves; Weight initialization sets the starting values of weights.
Key Concepts
Vanishing/Exploding Gradients Problem
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Deep Dive: Vanishing/Exploding Gradients Problem
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Definition
The vanishing/exploding gradients problem poses a challenge in training deep neural networks, hindering convergence during optimization. Techniques such as normalized initialization and intermediate normalization layers have been developed to mitigate this issue and enable the training of deep networks with improved convergence rates.
Topic Definition
The vanishing/exploding gradients problem poses a challenge in training deep neural networks, hindering convergence during optimization. Techniques such as normalized initialization and intermediate normalization layers have been developed to mitigate this issue and enable the training of deep networks with improved convergence rates.
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