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Building Grammatical Error Correction Models with Python

Name: Building Grammatical Error Correction Models with Python
Price: 59 USD
Author: Educative

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.

What's included

37 lessons across 8 modules
12 quizzes with instant feedback
in preconfigured environments
on every lesson

Join 3.1 million developers at

What you'll learn

An understanding of natural language distance techniques and how these are used in spell check systems
Hands-on experience building spellcheckers from scratch
An understanding of part-of-speech tagging and how it’s utilized in building grammar correction systems
An understanding of neural machine translation as a methodology for building modern grammar correction systems
Hands-on experience building transformer-based grammar correction systems using HuggingFace

Learning Roadmap

37 Lessons1 Project12 Quizzes11 Challenges

Introduction

Get familiar with grammar parsing, spell checking, and essential NLP terminology in Python.

Course Introduction

Essential Terminology

Edit Distance

Discover the logic behind edit distance, its algorithms, and practical NLP applications.

What Is Edit Distance?

Calculating Minimum Edit Distance

Implementation of Wagner-Fischer Algorithm

Distance Calculations in NLTK

Distance Calculations in Fuzzy

Summary: Edit Distance

Quiz: Edit Distance

Basic Spellchecker

8 Lessons

Examine spellchecker construction, models like Norvig's, and improve error correction accuracy.

Modern Spell Check Methods

5 Lessons

Apply your skills to modern spell check methods using SymSpell, machine learning, and transformers.

Part-of-Speech Tagging

6 Lessons

Map out the steps for POS tagging using HMMs, Viterbi, and NLTK tools.

Basic Grammatical Error Checking

5 Lessons

Simplify complex topics in rule-based grammar checking and POS tagging implementation.

Modern Grammar Error Correction Methods

3 Lessons

Practice using modern transformer-based methods for effective grammar error correction.

Project: Simple Transformer

Project

Conclusion

Step through the essential techniques and methods for developing grammatical error correction models.

Summary

Auto-Tagging System for Content Categorization

Project

Premium

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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