Input layer: Difference between revisions

In the input layer, [[activation function]]s are typically linear or nonexistent and pass on input data without modification. This is because most input data is raw and unprocessed; it's up to subsequent layers to extract meaningful information from it.

The input layer is the starting point of a [[machine learning model]], and it plays an integral role in its operation. It receives raw input data and passes it on to the next layer for further processing, ultimately producing meaningful information.

In a sense, the input layer acts as a link between raw input data and the final output produced by the model. Its task is to give the model all of the information it needs in order to make accurate predictions while simultaneously aiding its capacity for learning and improvement over time.