Introduction to Natural Language Processing

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 book will enable aspiring deep learning developers to handle massive amounts of data using NLP and TensorFlow. This chapter covers the following topics:

• What is Natural Language Processing?
• Tasks of Natural Language Processing
• The traditional approach to Natural Language Processing
• The deep learning approach to Natural Language Processing
• Introduction to the technical tools

In this chapter, we will provide an introduction to NLP and to the rest of the book. We will answer the question, “What is Natural Language Processing?”. Also, we’ll look at some of its most important use cases. We will 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 book and the technical tools we will be using.