Authors : LWANGA Derrick

Volume/Issue : Volume 7 - 2022, Issue 11 - November

Google Scholar : https://bit.ly/3IIfn9N

DOI : https://doi.org/10.5281/zenodo.7435130

Abstract : Human beings have always been fascinated by the future. Humans have been inspired to innovate by their desire to explore the future and learn about the unknown. Revenue are estimation normally depends on the sales of existing products. The sales forecast is one of the vital objectives in the business plan for any company. Sales forecasting is the process of determining the future revenue by using the prediction of the amount products sales. Success of the business usually depends on the amount of sales. Sales forecasting or revenue estimation is very important in the way that helps the company to determine the vital products or services which in return helps to reduce the costs of investing in non-profitable products. We needed to have a lot of information to develop sales predictions for a Bangalore Mart 250 supermarket each product previous sales records as a result, we acquired two year sales data from Bangalore Mart. The results of this research study was achieved through use of Machine Learning Models which include Linear Regression Random, Forest Regressor Lasso, Regressor Gradient, Boosting Regressor, Decision Tree Regressor and Ridge Regressor. Keywords: Machine learning, Mean Absolute Error, Mean Squared Error, Root Squared Error, Python, One Hot Encoding, Ridge Regressor, Lasso Regressor, Random Forest Regressor, Gradient boosting Regressor, Decision Tree Regressor. Sales Forecasting