Automated Flood Prediction ML

This project aims to predict flood occurrences based on various weather parameters. It includes data fetching, model training, and prediction scripts.

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Project Structure

.DS_Store
├── data/
│   ├── FloodPrediction.csv
├── models/
│   ├── flood_prediction_model.pkl
├── notebooks/
│   ├── flood_prediction.ipynb
├── scripts/
│   ├── data_fetcher.py
│   ├── run_pipeline.py
├── requirement.txt

Directory Breakdown

• 📂 data/ - Contains the dataset used for training and prediction.
• 📂 models/ - Stores the trained machine learning model.
• 📂 notebooks/ - Includes Jupyter notebooks for data exploration and model training.
• 📂 scripts/ - Houses Python scripts for data fetching and running the prediction pipeline.
• 📄 requirement.txt - Lists the dependencies required for the project.

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Setup

1️⃣ Clone the repository

git clone https://github.com/anujjainbatu/automated-flood-prediction-ml.git

2️⃣ Create a virtual environment

python3 -m venv venv
source venv/bin/activate  # For macOS/Linux
venv\Scripts\activate    # For Windows

3️⃣ Install dependencies

pip install -r requirement.txt

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Usage

📥 Data Fetching

To fetch the latest weather data and update the database, run:

python scripts/data_fetcher.py

🚀 Running the Prediction Pipeline

To execute the entire prediction pipeline, including data fetching, model prediction, and saving predictions to the database, run:

python scripts/run_pipeline.py

⏳ Automating with Cron Job

To automate the prediction pipeline with a cron job, add the following line to your crontab (e.g., to run the script every day at midnight):

0 0 * * * /usr/bin/python3 /path/to/your/workspace/scripts/run_pipeline.py

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📜 License

This project is licensed under the MIT License. See the LICENSE file for details.