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

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.

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git clone Navigate to the project directory.

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cd Set up a virtual environment (optional but recommended).

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python -m venv myenv Activate the virtual environment.

On Windows:

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myenv\Scripts\activate On macOS and Linux:

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source myenv/bin/activate Install the required packages.

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pip install -r requirements.txt Usage Run the Streamlit app.

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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.

Setup Make sure you have Python installed on your system.

Clone this repository to your local machine.

Copy code

git clone Navigate to the project directory.

Copy code

cd 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: [email protected]

Author

Sonny Agorvor-Otchie.