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Natural Language Processing with Python: a Step-by-Step Guide

Learn natural language processing with professional guidance!
Course from BitDegree
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How you can set up the natural language toolkit (NLTK) and use its basic features
How parsing natural language and inputting text with computer code works
How automatic text classification works and how to evaluate the classifier
How to perform fundamental text analysis

Most of us have used automatic translation systems (such as Google Translate), spell checking software, bots, or personal assistants (Siri and the like). What all these technologies have in common is natural language processing (NLP) – a type of artificial intelligence that reads and understands natural language, and then acts accordingly.

Most of these systems are trained via machine learning. Did you know you can do it too? Yes, it might seem complicated, but there’s no need to worry when you have a beginner-friendly NLP tutorial to follow! In this course, you will learn natural language processing with Python. You will not be asked to use any complex mathematical theories: all you need is some basics in Python programming language. If you do, you’re all set!

Before you learn natural language processing – how does it work?

To be able to perform natural language processing with Python, you need to understand what it entails. First and foremost, your system needs to be able to recognize and parse textual data. This way, it will be able to understand the text when you give it new pieces.

Next, you need to make the program able to analyze the text and provide a suitable answer: find the information the user asked for, translate their words, etc. Simple examples of NLP systems could be search engines or other information retrieval systems, as well as text analysis software of any kind.

Why perform natural language processing with Python?

The Python programming language has a great natural language toolkit, commonly named NLTK. It is a powerful library that allows you to:

  • Split up words and sentences (tokenize)
  • Recognize natural language
  • Identify the main subjects
  • Understand the main idea of the text

We will start our natural language processing tutorial by setting NLTK up. Then, you will get to know all the specifics of this library, including stemming and lemmatization.

Why choose this NLP Python tutorial in particular?

To a beginner, learning natural language processing with Python might seem like a complicated and even somewhat scary task. However, Frank Anemaet has done his best to make this course as beginner-friendly as possible. In just under an hour of video lectures, you will go through the whole process step-by-step.

Now, in the additional text file, you will find all the source codes for the examples shown in the lectures. You can use them as they are or write your own Python code and check for differences later! Of course, we would recommend the latter, as writing your own code makes it easier to learn natural language processing with Python. Still, we do know sometimes a person just lacks patience, and that’s okay – as long as you still analyze how and why exactly the code works.

After watching Frank Anemaet’s natural language processing tutorial, you will have a firm grasp on how you can build your own NLP systems. We promise – it will not be as hard as you think, and the result will turn out even more rewarding!

Natural Language Processing with Python: a Step-by-Step Guide
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