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Depth: Difference between revisions

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(Created page with "===Introduction== Depth is an essential concept in machine learning, particularly deep learning, where it refers to the number of layers within a neural network. Neural networks consist of interconnected artificial neurons that process and transform data. The depth of a network is determined by its number of layers and has an immense effect on its performance; more layers equals greater complexity for your model. ==What is depth in machine learning?== Machine learning e...")
 
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===Introduction==
==Introduction==
Depth is an essential concept in machine learning, particularly deep learning, where it refers to the number of layers within a neural network. Neural networks consist of interconnected artificial neurons that process and transform data. The depth of a network is determined by its number of layers and has an immense effect on its performance; more layers equals greater complexity for your model.
[[Depth]] is an essential concept in [[machine learning]], particularly [[deep learning]], where it refers to the number of [[layer]]s within a [[neural network]]. Neural networks consist of interconnected artificial [[neuron]]s that process and transform data. The depth of a network is determined by its number of layers and has an immense effect on its performance; more layers equals greater complexity for your model.
 
==How to Calculate Depth of a Neural Network==
Depth = number of [[hidden layers]] + number of [[output layer]]s (usually 1) + number of any [[embedding layer]]s
 
A neural network with 8 hidden layers and 1 output layer would have the depth of 9
 
*Note that [[input layer]] does not affect depth


==What is depth in machine learning?==
==What is depth in machine learning?==