What is the primary challenge associated with deeper networks in terms of training?
Understand the Problem
The question is asking about the primary challenge encountered when training deeper neural networks, with multiple choice options presented.
Answer
Vanishing/exploding gradients in network training.
The primary challenge with deeper networks in training is vanishing/exploding gradients, which can hinder the network's learning, especially in early layers.
Answer for screen readers
The primary challenge with deeper networks in training is vanishing/exploding gradients, which can hinder the network's learning, especially in early layers.
More Information
Vanishing gradients occur in deep networks because gradients used in training become extremely small, preventing effective update of weights. Exploding gradients involve gradients becoming too large, causing instability. Both impact the ability to train deep networks effectively.
Tips
A common mistake is not properly initializing weights or not using batch normalization, both of which can mitigate gradient issues.
Sources
- Challenges of Deep Neural Network Training - Kaggle - kaggle.com
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