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)

Requesting Content from Web Pages

Whenever you visit a web page from your web browser, you actually send a request to fetch its content. This can be done using Python scripts. Packages such as urllib3 and requests are used to do so. Let's look at an exercise to get a better understanding of this concept.

Exercise 41: Collecting Online Text Data

In this exercise, we will collect online data, with the help of requests and urllib3. Follow these steps to implement this exercise:

  1. Use the requests library to request the content of a book available online with the following set of commands:
    import requests
    r = requests.post('https://www.gutenberg.org/files/766/766-0.txt')
    r.status_code

    The preceding code generates the following output:

    Figure 4.10: HTTP status code

    Note

    Here, 200 indicates that we received a proper response from the URL.

  2. To locate the text content of the fetched file, write the following code:
    r.text[:1000]

    The preceding code generates the following...