In Keras, layers are the fundamental building blocks used to construct neural network models. Each layer in Keras performs a specific computation on the input data and produces an output. Layers can be thought of as the individual processing units that transform the input data into a more useful representation, ultimately leading to the desired output.
Here are some key points to understand about layers in Keras :
* Input and Output
* Types of Layers
* Dense (fully connected) layer
* Convolutional layer
* Recurrent layer
* Pooling layer
* Dropout layer
* Activation layer
* Parameters and Weights
* Layer Stacking
* Configurability
