Introduction: Natural Language Processing

Overview

Natural language processing (NLP) offers a much-needed set of tools and algorithms for understanding and processing the large volume of unstructured data in today’s world. Recently, deep learning has been widely adopted for many NLP tasks because of the remarkable performance deep learning algorithms have shown in a plethora of challenging tasks, such as image classification, speech recognition, and realistic text generation.

TensorFlow is one of the most intuitive and efficient deep learning frameworks currently in existence that enables such amazing feats. This course will enable aspiring deep learning developers to handle massive amounts of data using NLP and TensorFlow.

Flow of the topics

This chapter covers the following topics:

• What is NLP?
• Tasks of NLP
• The traditional approach to NLP
• The deep learning approach to NLP
• Introduction to the technical tools used for NLP

In this chapter, we’ll provide an introduction to NLP and to the rest of the course. We’ll answer the question, “What is natural language processing?” Also, we’ll look at some of its most important use cases. We’ll also consider the traditional approaches and the more recent deep learning-based approaches to NLP, including a fully connected neural network (FCNN). Finally, we will conclude with an overview of the rest of the course and the technical tools we will be using.