https://github.com/akibahmed229/weatherforecasting
Realtime Weather Forecasting using Machine Learning
https://github.com/akibahmed229/weatherforecasting
dijango linear-regression machine-learning python randomforestclassifier randomforestregressor
Last synced: 3 months ago
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Realtime Weather Forecasting using Machine Learning
- Host: GitHub
- URL: https://github.com/akibahmed229/weatherforecasting
- Owner: akibahmed229
- Created: 2024-10-28T19:09:04.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-11-05T08:12:21.000Z (7 months ago)
- Last Synced: 2025-01-15T04:40:00.943Z (5 months ago)
- Topics: dijango, linear-regression, machine-learning, python, randomforestclassifier, randomforestregressor
- Language: Jupyter Notebook
- Homepage:
- Size: 18.8 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Weather Forecasting Project
This project leverages machine learning to predict weather patterns, including rain forecasts and future temperature/humidity predictions, and displays them via a Django web interface.
## How to Run the Project
You can run the project using **Docker** or **Python**.
### Option 1: Using Docker
1. Clone the repository:
```bash
git clone https://github.com/akibahmed229/WeatherForecasting
```
2. Navigate to the project directory:
```bash
cd WeatherForecasting
```
3. Build and run the Docker container:
```bash
docker compose up
```
### Option 2: Using Python
1. Set up a virtual environment:
```bash
python -m venv ./venv
```
2. Activate the virtual environment:
- **Linux/macOS**:
```bash
source ./venv/bin/activate
```
- **Windows**:
```bash
.\venv\Scripts\activate
```
3. Install the required dependencies:
```bash
pip install -r requirements.txt
```
4. Run the Django server:
```bash
python manage.py runserver
```
### Access the Application
Once the server is running, you can access the application at:
```
http://localhost:8000
```