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language_identification_with_natural_language_processing-a_multilingual_text_analysis_project's Introduction

Language Identification with Natural Language Processing: A Multilingual Text Analysis Project

Language detection models enable multilingual support, personalized content, and global data analysis. They optimize translation services, enhance cybersecurity, and improve e-commerce and search engine functionality. Essential for efficient digital interactions, these models ensure precise communication and tailored user experiences across languages and applications.

Developed a Language Detection project utilizing Natural Language Processing (NLP) techniques. This project accurately identifies and categorizes text data into different languages.

How to Run

To execute the language detection model:

  1. File Overview: The project comprises 2 folders and 4 files.
  2. Download: Begin by downloading all files.
  3. Dataset: Utilize the Languages_detection_22000.csv dataset for model training.
  4. Jupyter Notebook: Access language_detection.ipynb to view and run the NLP model code.
  5. Configuration: Ensure to adjust file directories in the code to match your input data locations before execution.

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