What is the primary challenge associated with training very deep neural networks without any specialized techniques?
- Overfitting due to small model capacity
- Exploding gradients
- Vanishing gradients
- Slow convergence
The primary challenge of training very deep neural networks without specialized techniques is the vanishing gradient problem. As gradients are back-propagated through numerous layers, they can become extremely small, leading to slow convergence and making it difficult to train deep networks. Vanishing gradients hinder the ability of earlier layers to update their weights effectively.
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