hieuminh65 / Sale_Forecast_And_Trend_Vision

A model forecast sale growth of base on data of US Retail by Stores Type

Linear Regression for Revenue and Sales Forecasting

This project implements a Linear Regression model to forecast revenue and sales for businesses. The model has an accuracy rate of 90-99%.

Data

• The data is provided by the U.S. Census Bureau.
• This dataset provides information on retail and food services sales for the period of 1992 to 2021.
• All values in this report are in millions of dollars.

Usage

1. Put mains.py, function_main.py, and US_Retail_Sales_1992_2014.csv in the same folder.
2. Run mains.py file

python3 mains.py

3. When prompted, enter a year (after 2014) to predict and view the prediction results.