Implementing Different Layers
It is important to know how to implement different layers. In the prior recipe, we implemented fully connected layers. We will expand our knowledge of various layers in this recipe.
Getting ready
We have explored how to connect between data inputs and a fully connected hidden layer. There are more types of layers 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 as activation functions. Convolutional...
