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aniketwdubey / repository
The main motive of the project is to predict the amount of rainfall in Vidarbha region or state well in advance. We predict average rainfall using past data.
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The main motive of the project is to predict the amount of rainfall in Vidarbha region or state well in advance. We predict average rainfall using past data.
Clone the repository
Set up a virtual environment (optional but recommended):
python -m venv env
source env/bin/activate # On Windows, use `env\Scripts\activate`
Install required dependencies:
pip install -r requirements.txt
Train the model and create pickle file:
python app.py
This will train the model using the provided dataset and save it as a pickle file.
Run the Flask app:
python main.py
The Flask app will start running, typically on http://127.0.0.1:5000/.
XGBoost and Random Forest performed better compared to other models. However, if speed is an important thing to consider, we can stick with Random Forest instead of XGBoost.
Here we can collect more data and use neurals networks more computational power could be really useful for us.