Book Image

Natural Language Processing Fundamentals

By : Sohom Ghosh, Dwight Gunning
Book Image

Natural Language Processing Fundamentals

By: Sohom Ghosh, Dwight Gunning

Overview of this book

If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language.
Table of Contents (10 chapters)

History of NLP

NLP is an area that overlaps with others. It has emerged from fields such as artificial intelligence, linguistics, formal languages, and compilers. With the advancement of computing technologies and the increased availability of data, the way natural language is being processed has changed. Previously, a traditional rule-based system was used for computations. Today, computations on natural language are being done using machine learning and deep learning techniques.

The major work on machine learning-based NLP started during the 1980s. During the 1980s, developments across various disciplines such as artificial intelligence, linguistics, formal languages, and computations led to the emergence of an interdisciplinary subject called NLP. In the next section, we'll look at text analytics and how it differs from NLP.