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Machine Learning Glossary: Difference between revisions
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* Forward propagation - Inference through a neural network by computing each layer's outputs. | * Forward propagation - Inference through a neural network by computing each layer's outputs. | ||
* Fréchet Inception Distance (FID) - a reference-based distribution metric which passes images through a pretrained network (typically Inception) | |||
* Fully connected network - The standard neural network model where each layer is a sequence of nodes. | * Fully connected network - The standard neural network model where each layer is a sequence of nodes. | ||
* Features or Feature map - a generic term indicating the intermediate outputs of a neural network | * Features or Feature map - a generic term indicating the intermediate outputs of a neural network | ||