Weather Prediction Model (Streamlit App)
This project is a machine learning–based weather prediction system with an interactive Streamlit frontend.
It predicts future temperature values using historical weather data and regression techniques.
Live app: https://ak-weather-prediciton.streamlit.app/
Demo Screenshot:
Project Overview The goal of this project is to:
- Analyze historical weather data
- Train a regression-based ML model
- Predict future weather metrics (temperature)
- Provide an easy-to-use web interface for predictions
The backend model is trained using scikit-learn, and the frontend is built using Streamlit.
Features
- Predicts temperature using historical weather parameters
- Ridge Regression model to handle multicollinearity
- Interactive web UI built with Streamlit
- Model persistence using Joblib
- Fast and lightweight deployment
Tech Stack Machine Learning
- Python
- scikit-learn
- NumPy
- pandas
Model
- Linear Regression
- Features:
- Precipitation
- Snow
- Snow Depth
- Maximum Temperature
- Minimum Temperature
Frontend
- The application uses Streamlit for frontend development and deployment. Streamlit enables an interactive web interface where users can input weather features and receive predictions from the model.