Build a Language Detector

In this project, we will build a text-based language detector in Python to identify languages using Flask.

You will learn to:

Scrape data using Python.

Preprocess text data.

Create a language detection model without complex computations.

Create a simple Flask application.

Skills

Natural Language Processing

Text Preprocessing

Data Cleaning

Prerequisites

Intermediate knowledge of Python

Understanding of machine learning

Familiarity with text preprocessing

Basic understanding of NLP concepts and techniques

Technologies

Flask

Python

Project Description

This project aims to develop a language detection system capable of identifying the language of a given text document. The system utilizes n-grams, sequences of contiguous items (typically characters or words), to extract language-specific patterns from the text. It involves several stages: data collection from public domain books in various languages, text tokenization, n-gram generation, and language identification based on comparing n-grams frequencies with pretrained language models.

Technologies and libraries employed include Python libraries for text processing and web scraping. The end product is a language detection system capable of identifying the language of input text. The application’s modularity allows for easy expansion with additional languages and, hence, a better language identification system.

Project Tasks

Introduction

Task 0: Get Started

Task 1: Import Libraries

Downloading and Preprocessing Data

Task 2: Get the Data

Task 3: Preprocess the Data

Frequency Profiling

Task 4: Generate N-Grams

Task 5: Count and Sort N-Grams by Frequency

Task 6: Call N-Grams Functions

Language Detection

Task 7: Preprocess the Test File

Task 8: Test the Model

Language Detection Application

Task 9: Create Frontend of the Application

Task 10: Handle and Route the Request Object

Congratulations!

Relevant Courses

Use the following content to review prerequisites or explore specific concepts in detail.