Natural Language Processing With TextBlob (Python NLP)

Learn how to perform NLP with one of the most popular NLP frameworks — TextBlob. This course is in 100% Python

TextBlob is an open-source Python package built on top of NLTK, which is perhaps the most well-known NLP framework. TextBlob allows you to complete common NLP tasks with just a few lines of code and with minimal complexities. So, whether you’re a beginner looking to learn NLP or a professional who wants to learn a tool to simplify your life — this course is for you.

What you’ll learn

  • Natural Language Processing (NLP).
  • TextBlob — a Python framework built on top of NLTK.
  • Tokenization.
  • Text classification.
  • Part-of-speech tagging.
  • Producing definitions.
  • Comparing the similarity of words.
  • Generating n-grams.
  • Spell checking.
  • Sentiment analysis.
  • Hugging Face’s Datasets library.

Course Content

  • Introduction –> 1 lecture • 1min.
  • TextBlob Basics –> 6 lectures • 19min.
  • WordNet –> 6 lectures • 17min.
  • Fundmental NLP Tasks –> 7 lectures • 20min.
  • Text Classification –> 6 lectures • 21min.
  • Conclusion –> 2 lectures • 1min.

Natural Language Processing With TextBlob (Python NLP)

Requirements

  • A solid understanding of basic Python syntax.
  • A Google account (for Google Colab).

TextBlob is an open-source Python package built on top of NLTK, which is perhaps the most well-known NLP framework. TextBlob allows you to complete common NLP tasks with just a few lines of code and with minimal complexities. So, whether you’re a beginner looking to learn NLP or a professional who wants to learn a tool to simplify your life — this course is for you.

TextBlob is one of the most popular NLP Python packages with over 7700 stars on GitHub and over 10M downloads.

 

This course will cover:

  1. Text classification
  2. Tokenization
  3. Part-of-speech tagging
  4. Getting synonyms
  5. Producing definitions
  6. Comparing the similarity of words
  7. Spell checking
  8. Generating n-grams
  9. Sentiment analysis
  10. Fetching data from Hugging Face’s dataset distribution network 

    AND MORE ALL WITH TEXTBLOB!!

     

Installations:

NONE!!! This is done entirely in Google Colab, which is web based.

 

About the instructor:

My name is Eric Fillion, and I’m from Canada. I’m on a mission to make state-of-the-art advances in the field of NLP through creating open-source tools and by creating educational content. In early 2020, I led a team that launched an open-source Python Package called Happy Transformer. Happy Transformer allows programmers to implement and train state-of-the-art Transformer models with just a few lines of code. Since its release, it has won awards and has been downloaded over 17k times.

Requirements:

  • A basic understanding of Python
  • A google account — for Google Colab

 

What Now?

I’ve made all of the introductory lectures for each section available for free preview. So, check them out, and I’m looking forward to seeing you in the course!

Get Tutorial