🌍 Name Predictor by Country

This project is a Name Predictor that determines the likely country or origin of a given name using a Recurrent Neural Network (RNN). It provides predictions with adjustable top-N probabilities, allowing users to see the most probable countries for a given name.

🚀 Features

• Predicts the country of origin for a given name.

• Supports adjustable top-N predictions with probabilities.

• Simple command-line interface for predictions.

📂 Project Structure

.
├── models/
│   └── best_model.pt      # Trained model saved here
├── data/
│   ├── names/
│   │   ├── English.txt    # Sample data file
│   │   ├── French.txt
│   │   └── ...            # Additional country data files
├── train.py               # Training script with early stopping
├── predict.py             # Prediction script with adjustable top-N predictions
├── model.py               # RNN model definition
├── data.py                # Data processing and augmentation
├── requirements.txt       # Python dependencies
└── README.md              # This file

📦 Prerequisites

Ensure you have the following installed:

• Python 3.7+
• pip (Python package installer)

🛠️ Installation

1. Clone the repository:

   git clone https://github.com/yourusername/name_predictor_from_country.git
   cd name_predictor_from_country

2. Install the dependencies:

   pip install -r requirements.txt

3. Prepare your dataset:

   • Place your dataset files in the data/names/ directory. Each file should be named according to the country it represents (e.g., English.txt, French.txt).
   • Each file should contain one name per line.

📊 Training the Model

To train the model, simply run:

python train.py

Training

• The best model will be saved in the models/ directory as best_model.pt.

Example Output:

5000 5% (0m 5s) 2.7754 Vourlis / Greek ✓
10000 10% (0m 10s) 3.1260 CrespA / Italian ✗ (Portuguese)
...

Training complete. Best model saved with loss: 2.5479

🔮 Making Predictions

To predict the country of origin for a name, use the predict.py script.

Usage:

python predict.py <name> [num_predictions]

• <name>: The name you want to predict the country for.
• [num_predictions] (optional): Number of top predictions to show (default is 3).

Example:

python predict.py anitha 5

Example Output:

Top 5 predictions for the name 'anitha':
1: Indian with probability 0.4597
2: Japanese with probability 0.1845
3: Portuguese with probability 0.1139
4: Arabic with probability 0.0767
5: Spanish with probability 0.0734