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Vanishing/Exploding Gradients Problem
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Arrange the following steps in addressing the vanishing/exploding gradients problem in deep neural networks from first to last: A) Implement normalization techniques, B) Train the network, C) Initialize weights appropriately, D) Monitor gradient behavior during training.

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A

C → A → D → B

B

A → C → D → B

C

D → A → C → B

D

B → C → A → D

Understanding the Answer

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First set the weights carefully. Other options are incorrect because This answer puts normalization before weight initialization; This answer starts by watching gradients before any changes.

Key Concepts

Vanishing/Exploding Gradients Problem
Neural Network Training Techniques
Weight Initialization Methods
Topic

Vanishing/Exploding Gradients Problem

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medium level question

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Definition
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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