Learn to build spell checkers and grammar correction models using Python. Explore NLP packages, POS tagging, heuristic methods, and transformer-based spellcheckers for practical use.

Spell Check and Grammar Parsing using Natural Language Processing.png

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python3.7

In this course, you’ll learn the details of spell check and grammatical error correction systems by creating them with their basic building blocks. You’ll explore natural language processing packages like NLTK, pandas, spaCy, Fuzz, GECToR, HuggingFace, and more. 

You’ll build the Norvig spellchecker and understand how modern machine learning-based spellcheckers work. This is followed by the mathematical concepts required for identifying part-of-speech (POS) tags for grammatical error checking. You’ll then implement a POS rule-based grammar checker, using a heuristic-based approach to correct grammar mistakes. Finally, you’ll learn to develop a transformer-based spellchecker using HuggingFace’s transformer libraries through a hands-on final project.

After completing this course, you’ll fully understand how modern spellcheckers and grammar correction software work and how these can be integrated into natural language corrector systems such as Grammarly.

Building Grammatical Error Correction Models with Python

In the context of a spellchecker, a **language model** refers to a statistical model trained on a large corpus of text data to estimate the likelihood of word sequences in a specific language. It helps the spellchecker make intelligent suggestions for correcting misspelled words by considering the context in which the word appears. The equation is represented by $P(c)$, or the probability that $c$ appears as a word of text.

As a reminder, our overall equation is:
$$\underset{c \ \in \ \text{candidates}} { \text{ arg\ max}} \ P(c) P(w|c).$$

Understand what a language model is and where it fits into a spellchecker. Learn how to implement a language model.

Introduction

Edit Distance

Basic Spellchecker

Modern Spell Check Methods

Part-of-Speech Tagging

Basic Grammatical Error Checking

Modern Grammar Error Correction Methods

Project: Simple Transformer

Conclusion

Auto-Tagging System for Content Categorization

Language Model

What is a language model?