Manuscript Number : SHISRRJ247271

E-commerce platforms are developing more quickly as a result of the expanding impact of the Internet on people's lives. Both the number of users and the revenue generated by these platforms are trending upward. Strong government policy support in recent years has also created a favourable atmosphere for the growth of the e-commerce sector. The e-commerce sector has played a more significant part in the growth of the national economy as a result of this year's epidemic. In these situations, e-commerce platforms and businesses are growing in quantity and competitiveness. A platform needs to be able to better match user needs and perform well in all areas of coordination in order to keep its competitive advantage. Let’s consider a problem statement, an e-commerce company wants to increase its sells to a certain amount. Now the challenge is to find the amount of investment on advertisement that will result the gain in sells. This project involves building the sales estimator for a company which utilizes the value of the money invested to predict the sales get by advertisements. The Sales Estimation Project is an innovative application developed using Python programming language aimed at assisting businesses in accurately forecasting their sales figures. This abstract provides an overview of the project's objectives, functionalities, and significance. The main objective of the Sales Estimation Project's goal is to leverage data analysis additionally machine learning techniques to predict based on past sales, projected sales data, industry patterns, and more pertinent elements. By harnessing the power of Python libraries like Scikit-learn, NumPy, and Pandas, the project offers advanced analytical capabilities for generating accurate sales forecasts. Key functionalities of the Sales Estimation Project include feature engineering, model training, evaluation, and data preprocessing. The project supports various machine learning algorithms In conclusion, the Sales Estimation Project serves as a useful instrument for companies seeking to enhance their sales forecasting accuracy additionally make data-driven decisions. By harnessing the capabilities of Python programming language and machine learning algorithms, the project empowers businesses to optimize their operations and achieve better sales outcomes.