🚀 Migration Trends Prediction System

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📌 Project Description

The Migration Trends Prediction System is a machine learning–powered web application built with Flask.
It predicts migration trends using trained ML models and provides data-driven insights based on historical migration data.

This project integrates:

• Machine Learning model (.h5)
• Data preprocessing tools (scaler.pkl, label_encoder.pkl)
• Interactive web interface (Flask + HTML templates)
• Prediction output storage (predictions.json)

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⚙️ Features

• 📊 Migration trend prediction using ML model
• 🧠 Pre-trained model integration (final_model.h5)
• 🔄 Data preprocessing with scaler and encoder
• 🌐 Web-based interface (Flask)
• 📁 Structured output storage
• 📈 Support for analysis and visualization

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📂 Project Structure

migration/ │ ├── instance/ # Instance-specific configuration ├── static/ # CSS, JS, images ├── templates/ # HTML templates │ ├── app.py # Main Flask application ├── final_model.h5 # Trained ML model ├── label_encoder.pkl # Label encoder ├── scaler.pkl # Feature scaler ├── predictions.json # Prediction outputs ├── migration_trends_patch.diff ├── requirements.txt # Dependencies ├── read.txt # Documentation └── git # Git-related file/folder

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🛠️ Installation & Setup

1. Clone Repository

git clone https://github.com/Beke1e/migration.git
cd migration
2. Create Virtual Environment
python -m venv venv
# OR (specific version)
python3.10 -m venv venv
3. Activate Virtual Environment
.\venv\Scripts\activate
4. Install Dependencies
pip install -r requirements.txt
5. Run the Application
python app.py

🧠 Technologies Used
Python 🐍
Flask 🌐
Scikit-learn 🤖
Pandas & NumPy 📊
HTML/CSS/JavaScript 🎨