Sentence Classification with Convolutional Neural Networks

In this chapter, we will discuss a type of neural network known as Convolutional Neural Networks (CNNs). CNNs are quite different from fully connected neural networks and have achieved state-of-the-art performance in numerous tasks. These tasks include image classification, object detection, speech recognition, and of course, sentence classification. One of the main advantages of CNNs is that, compared to a fully connected layer, a convolution layer in a CNN has a much smaller number of parameters. This allows us to build deeper models without worrying about memory overflow. Also, deeper models usually lead to better performance.

We will introduce you to what a CNN is in detail by discussing different components found in a CNN and what makes CNNs different from their fully connected counterparts. Then we will discuss the various operations used in CNNs, such as the convolution and pooling operations, and certain hyperparameters...