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)

Why is Sentiment Analysis Required?

In machine learning projects, we try to build applications that work, to a certain extent, similarly to a human being. We measure success in part by seeing how close our application is to matching human-level performance. Generally speaking, machine learning programs cannot exceed human-level performance by a significant margin, especially if our training data source is human generated.

Let's say, therefore, that we want to carry out sentiment analysis of product reviews. The sentiment analysis program should keep detect how reviewers feel. Of book, it is impractical for a person to read thousands of movie reviews. This is where automated sentiment analysis comes into picture. Artificial intelligence is useful when it is impractical for people to do some work. In this case, the work is reading thousands of reviews.