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: 3 months 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 (8 months ago)
• Default Branch: main
• Last Pushed: 2024-12-13T12:58:07.000Z (7 months ago)
• Last Synced: 2025-02-07T12:38:29.306Z (5 months ago)
• Topics: machine-learning, machinelearning, numpy, pandas, programming, python, scikit-learn, scikitlearn-machine-learning, weather-prediction
• Language: Python
• Homepage:
• Size: 176 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 1
• 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