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license: mit
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# Language_Detection - Multilingual Text Classification Dataset

This dataset is a collection of multilingual text samples designed for training and predicting languages in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Data Science (DS) applications. It contains labeled data that associates text samples with their respective languages, enabling language detection and classification tasks.

## Dataset Overview

The dataset consists of two columns:  

1. **Text**: A column containing text samples in various languages.  
2. **Languages**: A column specifying the corresponding language for each text sample.

### Example
| Text                          | Languages   |
|-------------------------------|-------------|
| Bonjour tout le monde         | French      |
| Hello, world!                 | English     |
| 你好，世界！                    | Chinese     |
| வணக்கம் உலகம்                  | Tamil       |
| Hola, mundo                   | Spanish     |

## Features

This dataset also achieves a 97% accuracy and a 98.4% sensitivity score.

- **Multilingual Coverage**: Includes text samples from multiple languages, covering diverse linguistic structures and scripts.
- **Clean and Structured**: Organized in a CSV format, making it easy to integrate into AI/ML pipelines.
- **Versatile Applications**: Suitable for language classification, sentiment analysis, and natural language processing tasks.

## Applications

1. **Language Detection**: Train models to identify the language of a given text sample.  
2. **Multilingual NLP**: Build NLP models capable of handling diverse languages.  
3. **Data Analysis**: Analyze linguistic diversity and patterns in text data.  
4. **Transfer Learning**: Fine-tune pre-trained language models like BERT or GPT on this dataset.  

## Dataset Format

- **File Type**: CSV  
- **Columns**:  
  - `Text`: Multilingual text samples (string).  
  - `Languages`: Corresponding language labels (string).  

## License

This dataset is released under the [MIT License](LICENSE). You are free to use, modify, and distribute it for any purpose, provided proper attribution is given.