Neural Network Projects with Python

Layers – the atom of neural networks in Keras

You can think of layers in Keras as an atom, because they are the smallest unit of our neural network. Each layer takes in an input performs a mathematical function, then outputs that for the next layer. The core layers in Keras includes dense layers, activation layers, and dropout layers. There are other layers that are more complex, including convolutional layers and pooling layers. In this book, you will be exposed to projects that uses all these layers.

For now, let's take a closer look at dense layers, which are by far the most common type of layer used in Keras. A dense layer is also known as a fully-connected layer. It is fully-connected because it uses all of its input (as opposed to ...