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)

Introduction

One huge challenge when dealing with text data is that data can be huge in size and can come in various forms, such as documents, emails, and web pages. Reading and understanding such data is a cumbersome task. Also, people tend to be less patient when it comes to reading huge amounts of information; they prefer to consume information in bite-size chunks. For instance, Twitter has doubled its character limit, but it is still only 280 characters. Our interactions over Instagram, Facebook, Snapchat, and other social media platforms have got us accustomed to reading concise text.

Due to this change in habits, there is a need to reduce the volume of content that we ask people to read while still retaining the central ideas of the content. To aid this, content providers sport features such as text summaries that provide users with the gist of information.

Therefore, there is a big business need to automate text summarization. In the coming sections, we will explore text...