# 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.

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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:

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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.

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.