What are hidden layers in neural networks and what are their types?
Hidden layers in neural networks are intermediate layers that process and transform input data to enable the network to learn and make predictions. Different types of hidden layers, such as fully connected, convolutional, and recurrent layers, contribute to various aspects of data processing, making neural networks versatile and powerful in tasks like image recognition, sequence…