Deep Learning Essentials

Advanced Natural Language Processing

In the previous chapter, we covered the basics of natural language processing (NLP). We covered simple representations of text in the form of the bag-of-words model, and more advanced word embedding representations that capture the semantic properties of the text. This chapter aims to build upon word representation techniques by taking a more model-centric approach to text processing. We will go over some of the core models, such as recurrent neural networks (RNNs) and Long Short-Term Memory (LSTM) networks. We will specifically answer the following questions:

• What are some core deep learning models for understanding text?
• What core concepts form the basis for understanding RNNs?
• What core concepts form ...