Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/sundanc/weatherprediction
This project implements a weather prediction system that predicts the temperature based on real-time weather data, including features like humidity, wind speed, and day-related features (day of the week, month
https://github.com/sundanc/weatherprediction
machine-learning machinelearning numpy pandas programming python scikit-learn scikitlearn-machine-learning weather-prediction
Last synced: 27 days ago
JSON representation
This project implements a weather prediction system that predicts the temperature based on real-time weather data, including features like humidity, wind speed, and day-related features (day of the week, month
- Host: GitHub
- URL: https://github.com/sundanc/weatherprediction
- Owner: sundanc
- License: mit
- Created: 2024-11-29T08:00:03.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-12-13T09:48:06.000Z (28 days ago)
- Last Synced: 2024-12-13T10:41:00.586Z (28 days ago)
- Topics: machine-learning, machinelearning, numpy, pandas, programming, python, scikit-learn, scikitlearn-machine-learning, weather-prediction
- Language: Python
- Homepage:
- Size: 166 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# Weather Prediction App
This project implements a weather prediction system that predicts the temperature based on real-time weather data, including features like humidity, wind speed, and day-related features (day of the week, month). It uses a pre-trained machine learning model (SGD Regressor) to predict the temperature and compares the predicted temperature with the actual temperature fetched from a public weather API (OpenWeatherMap).
## Features
- Fetch real-time weather data for a specific city.
- Predict the temperature using a pre-trained machine learning model.![image](https://github.com/user-attachments/assets/4ad38c0a-042c-4c06-91c1-f4206803f6d5)
- Display actual vs predicted temperatures using a line chart.
- Show model performance metrics (Mean Absolute Error, Mean Squared Error).![image](https://github.com/user-attachments/assets/802afd49-d338-4f9d-b4d9-4af6713a29a2)
- Interactive user interface using Streamlit.## Requirements
- Python 3.8+
- `pandas`
- `streamlit`
- `requests`
- `scikit-learn`
- `joblib`You can install the required dependencies using the following command:
```bash
pip install -r requirements.txt