Book Image

The Natural Language Processing Workshop

By : Rohan Chopra, Aniruddha M. Godbole, Nipun Sadvilkar, Muzaffar Bashir Shah, Sohom Ghosh, Dwight Gunning
5 (1)
Book Image

The Natural Language Processing Workshop

5 (1)
By: Rohan Chopra, Aniruddha M. Godbole, Nipun Sadvilkar, Muzaffar Bashir Shah, Sohom Ghosh, Dwight Gunning

Overview of this book

Do you want to learn how to communicate with computer systems using Natural Language Processing (NLP) techniques, or make a machine understand human sentiments? Do you want to build applications like Siri, Alexa, or chatbots, even if you’ve never done it before? With The Natural Language Processing Workshop, you can expect to make consistent progress as a beginner, and get up to speed in an interactive way, with the help of hands-on activities and fun exercises. The book starts with an introduction to NLP. You’ll study different approaches to NLP tasks, and perform exercises in Python to understand the process of preparing datasets for NLP models. Next, you’ll use advanced NLP algorithms and visualization techniques to collect datasets from open websites, and to summarize and generate random text from a document. In the final chapters, you’ll use NLP to create a chatbot that detects positive or negative sentiment in text documents such as movie reviews. By the end of this book, you’ll be equipped with the essential NLP tools and techniques you need to solve common business problems that involve processing text.
Table of Contents (10 chapters)
Preface

The textblob library

textblob is a Python library used for NLP, as we've seen in the previous chapters. It has a simple API and is probably the easiest way to begin with sentiment analysis. textblob is built on top of the NLTK library but is much easier to use. In the following sections, we will do an exercise and an activity to get a better understanding of how we can use textblob for sentiment analysis.

Exercise 8.01: Basic Sentiment Analysis Using the textblob Library

In this exercise, we will perform sentiment analysis on a given text. For this, we will be using the TextBlob class of the textblob library. Follow these steps to complete this exercise:

  1. Open a Jupyter notebook.
  2. Insert a new cell and add the following code to implement to import the TextBlob class from the textblob library:
    from textblob import TextBlob
  3. Create a variable named sentence and assign it a string. Insert a new cell and add the following code to implement this:
    sentence = "but...