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Related Questions
- What are the primary factors that influence the size and computational complexity of a neural network's architecture?
- How does the choice of activation function impact the representational power of a neural network?
- Can you explain the trade-offs between using linear, ReLU, and other activation functions in terms of computational cost and model complexity?
- How do different layer types, such as convolutional, recurrent, and fully connected layers, affect the size and computational requirements of a neural network?
- What is the impact of using pre-activation vs. post-activation in a neural network on computational requirements?
- Can you discuss the effects of adding skip connections or residual connections on the size and computational complexity of a neural network?
- How do the number of hidden layers and the number of units per layer influence the size and computational requirements of a neural network?
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