US $19.97

Natural Language Processing in Python Using NLTK

——   Created by Ali Feizollah

Learn how to pre-process your text data and build topic modeling, text summarization and sentiment analysis applications

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2h 45m
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More about this course

Text mining and Natural Language Processing (NLP) are among the most active research areas. Pre-processing your text data before feeding it to an algorithm is a crucial part of NLP. In this course, you will learn NLP using natural language toolkit (NLTK), which is part of the Python. You will learn pre-processing of data to make it ready for any NLP application.

We go through text cleaning, stemming, lemmatization, part of speech tagging, and stop words removal. The difference between this course and others is that this course dives deep into the NLTK, instead of teaching everything in a fast pace.

This course has 3 sections. In the first section, you will learn the definition of NLP and its applications. Additionally, you will learn how to install NLTK and learn about its components.

In the second section, you will learn the core functions of NLTK and its methods and techniques. We examine different available algorithms for pre-processing text data.

In the last section, we will build 3 NLP applications using the methods we learnt in the previous section.

Specifically, we will go through developing a topic modeling application to identify topics in a large text. We will identify main topics discussed in a large corpus.

Then, we will build a text summarization application. We will teach the computer to summarize the large text and to summarize the important points.

The last application is about sentiment analysis. Sentiment analysis in Python is a very popular application that can be used on variety of text data. One of its applications is Twitter sentiment analysis. Since tweets are short piece of text, they are ideal for sentiment analysis. We will go through building a sentiment analysis system in the last example.

Finally, we compare NLTK with SpaCy, which is another popular NLP library in Python. It's going to be a very exciting course. Let's start learning.

The course project

Please select a dataset and apply sentiment analysis, text summarization, and topic modeling methods.

Please upload your results here.

27 Lessons

3 mins
free preview
3 mins
Course Overview
free preview
2 mins
Before You Start This Course
free preview
3 mins
What is NLP
7 mins
Applications of NLP
12 mins
Python Lists
7 mins
Python Strings
3 mins
Python Functions
10 mins
NLTK Installation
8 mins
Whats text wrangling
free preview
4 mins
Text Cleansing
9 mins
Sentence Tokenization
5 mins
Word Tokenization
7 mins
6 mins
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100% of 1 people enjoyed this course!

Akbari Mashkool liked this class and said...

good class

About the instructor

Ali Feizollah
Ali Feizollah
  • 1 review
  • 2 courses

I finished my PhD in computer science and now I'm a postdoc conducting research. I have over 7 years’ experience in research and article writing. …

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Class benefits

  • Certificate of Completion
  • 30 day satisfaction guarantee
  • 24/7 streaming access
  • Project included
  • Direct teacher access
  • 2h 45m of on-demand video
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