https://github.com/samadpls/goldpredictapi

FastAPI-based gold price prediction system using machine learning. Trained model and API for seamless usability. 📈🤖
https://github.com/samadpls/goldpredictapi

api fastapi gold-price-prediction machine-learning pydantic regression-models swagger-ui

Last synced: 6 months ago
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FastAPI-based gold price prediction system using machine learning. Trained model and API for seamless usability. 📈🤖

• Host: GitHub
• URL: https://github.com/samadpls/goldpredictapi
• Owner: samadpls
• License: mit
• Created: 2024-01-02T19:29:21.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2024-01-02T19:37:28.000Z (about 2 years ago)
• Last Synced: 2025-02-12T07:49:35.833Z (11 months ago)
• Topics: api, fastapi, gold-price-prediction, machine-learning, pydantic, regression-models, swagger-ui
• Language: Jupyter Notebook
• Homepage:
• Size: 3.6 MB
• Stars: 8
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# GoldPredictAPI 📈🤖

This project implements a gold price prediction system using machine learning. The system is trained on historical gold price data and provides a `FastAPI`-based API for making predictions.

## Files 📂

- **gld_predication.py**: FastAPI app with a pre-trained model, offering an API endpoint for gold price predictions.

- **Gold Price Prediction.ipynb**: Jupyter Notebook for initial gold price data exploration, preprocessing, and training of the RandomForestRegressor model.

## Dependencies 🛠️

- FastAPI

- Scikit-learn

- NumPy

- Pandas

- Matplotlib

- Seaborn

## How to Use 🚀

1. Install dependencies:

    ```bash

    pip install -r requirements.txt

    ```

2. Run the FastAPI application:

    ```bash

    uvicorn gld_predication:app --reload

    ```

    This will start the FastAPI server locally.

3. Make predictions using Swagger:

    Open your web browser and go to [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs) to access the Swagger UI.

    - Click on the `/predict` endpoint.

    - Click on the "Try it out" button.

    - Input the sample request data:

        ```json

        {

          "SPX": 2671.91992,

          "USO": 14.0600,

          "SLV": 15.5100,

          "EUR_USD": 1.186789

        }

        ```

    - Click on the "Execute" button to make a prediction.

      ![demo](https://github.com/samadpls/GoldPredictAPI/assets/94792103/0876bea2-aa30-4a63-a0a7-0e75badc699f)

4. Make predictions using curl:

    Alternatively, you can use `curl` to make predictions:

    ```bash

    curl -X 'POST' \

      'http://127.0.0.1:8000/predict' \

      -H 'accept: application/json' \

      -H 'Content-Type: application/json' \

      -d '{

      "SPX": 2671.91992,

      "USO": 14.0600,

      "SLV": 15.5100,

      "EUR_USD": 1.186789

    }'

    ```

## Additional Information ℹ️

- **Colab Notebook**: The `Gold Price Prediction.ipynb` file in Google Colab contains the initial exploration and model training.

- **Model Saving**: The trained model is saved as `gld_data.pkl` using the `pickle` library and loaded by the FastAPI application for predictions.

## License 📄

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

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