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)

Types of Data

To deal with data effectively, we need to understand the various forms in which it exists. Let's first understand the types of data that exist. There are two main ways to categorize data, by structure and by content, as explained in the upcoming sections.

Categorizing Data Based on Structure

On the basis of structure, data can be divided into three categories, namely structured, semi-structured, and unstructured, as shown in the following diagram:

Figure 2.1: Categorization based on content

These three categories are explained in detail here:

  • Structured Data: This is the most organized form of data. It is represented in tabular formats such as Excel files and Comma-Separated Value (CSV) files. The following figure shows what structured data usually looks like:
Figure 2.2: Structured data
  • Semi-Structured Data: This type of data is not presented in a tabular structure, but it can be represented...