| # Streamlit Web App For Sales Prediction | |
| # LP4 Embedding a machine learning model in a GUI | |
| *short project description* | |
| ## Summary | |
| | Code | Name | Published Article | Deployed App | | |
| |-----------|-------------|:-------------:|------:| | |
| | LP4 Embedding a machine learning model in a GUI|streamlit-web-app-for-sales-prediction| [Article]https://medium.com/@otchie.sonny/building-streamlit-web-app-for-sales-prediction-with-facebook-prophet-26c84ed8f625 | [Deployed App](http://localhost:8503) | | |
| | | |
| ## Description | |
| Favorita Stores Sales Prediction App | |
| This web application allows users to predict sales for Favorita stores based on historical data using the Facebook Prophet machine learning model. Users can input a specific date, and the app will provide a sales prediction for that date. | |
| Setup | |
| Make sure you have Python installed on your system. | |
| Clone this repository to your local machine. | |
| Copy code | |
| git clone <repository-url> | |
| Navigate to the project directory. | |
| Copy code | |
| cd <project-directory> | |
| Set up a virtual environment (optional but recommended). | |
| Copy code | |
| python -m venv myenv | |
| Activate the virtual environment. | |
| On Windows: | |
| Copy code | |
| myenv\Scripts\activate | |
| On macOS and Linux: | |
| Copy code | |
| source myenv/bin/activate | |
| Install the required packages. | |
| Copy code | |
| pip install -r requirements.txt | |
| Usage | |
| Run the Streamlit app. | |
| Copy code | |
| streamlit run sales_prediction_app.py | |
| The app will start a local web server, and you can access it by opening the provided URL in your browser. | |
| Once the app is loaded, you can select a specific date from the sidebar. | |
| The app will then display the predicted sales for that date based on the historical data and the trained Prophet model. | |
| Contributing | |
| Contributions to this project are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request. | |
| Favorita Stores Sales Prediction App | |
| This web application allows users to predict sales for Favorita stores based on historical data using the Facebook Prophet machine learning model. Users can input a specific date, and the app will provide a sales prediction for that date. | |
| Setup | |
| Make sure you have Python installed on your system. | |
| Clone this repository to your local machine. | |
| Copy code | |
| git clone <repository-url> | |
| Navigate to the project directory. | |
| Copy code | |
| cd <project-directory> | |
| Set up a virtual environment (optional but recommended). | |
| Copy code | |
| python -m venv myenv | |
| Activate the virtual environment. | |
| On Windows: | |
| Copy code | |
| myenv\Scripts\activate | |
| On macOS and Linux: | |
| Copy code | |
| source myenv/bin/activate | |
| Install the required packages. | |
| Copy code | |
| pip install -r requirements.txt | |
| Usage | |
| Run the Streamlit app. | |
| Copy code | |
| streamlit run sales_prediction_app.py | |
| The app will start a local web server, and you can access it by opening the provided URL in your browser. | |
| Once the app is loaded, you can select a specific date from the sidebar. | |
| The app will then display the predicted sales for that date based on the historical data and the trained Prophet model. | |
| Contributing | |
| Contributions to this project are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request. | |
| Feel free to customize the read.md file based on your specific project details and requirements. | |
| Please make sure to update tests as appropriate. Contact me via my email: otchie.sonny@gmail.com | |
| ## Author | |
| Sonny Agorvor-Otchie. | |