We have explored how to connect data inputs and a fully-connected hidden layer, but there are more types of layer that are built-in functions inside TensorFlow. The most popular layers that are used are convolutional layers and maxpool layers. We will show you how to create and use such layers with input data and with fully-connected data. First, we will look at how to use these layers on one-dimensional data, and then on two-dimensional data.
While neural networks can be layered in any fashion, one of the most common uses is to use convolutional layers and fully-connected layers to first create features. If we have too many features, it is common to have a maxpool layer. After these layers, non-linear layers are commonly introduced ...
