Learning Path
Question & Answer
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By simplifying the network architecture for easier deployment
By allowing deeper models to retain input information more effectively
By increasing the number of parameters in the model
By eliminating the need for data preprocessing
Understanding the Answer
Let's break down why this is correct
Identity mapping lets each layer pass the original input straight through. Other options are incorrect because Identity mapping does not make the network simpler; Identity mapping does not add many parameters.
Key Concepts
Identity Mapping in Deep Models
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Deep Dive: Identity Mapping in Deep Models
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Definition
Identity mapping is a technique used in constructing deeper models by adding layers that maintain the identity mapping from shallower models. This approach helps alleviate optimization challenges associated with increasing network depth and can lead to improved training error rates in very deep neural networks.
Topic Definition
Identity mapping is a technique used in constructing deeper models by adding layers that maintain the identity mapping from shallower models. This approach helps alleviate optimization challenges associated with increasing network depth and can lead to improved training error rates in very deep neural networks.
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