• Mohammad Ahsan Khan
• Aman Tiwari
• Danish Mushtaq Baig
• Karine Vinay Kumar
• Dr. Kamal Nain Sharma

Abstract—Sales forecasting is a typical function which more often than not revolves around the process of asking about the number of items sold or popularity of a product in some period of time. Making such revenue forecasts enables companies to have more realistic budgets, as data analysis facilitates informed formulation of strategic plans for the future. Budget, revenue allocation, and future advents strategies are all affected by the revenue forecasts that are produced, as another reflection of its key role. Contrasting with the category of targets above, the expected sales are the assumptions about the business performance in the future which immigrants from the historic performance data, available trends, and improvement initiatives for a verification of accuracy. In this evaluation, two different kinds of forecasts: digital and shopper, is analyzed by applying machine learning algorithms in a European retail drug-store chain for a 6-weeks period. We implement machine learning techniques and data analysis to build a very useful instrument which predicts store sales to managers on time and fills their schedules with efficient employees to promote productivity. Libraries of Python programming and math machine implements — matplotlib, scikit-learn, NumPy and Pandas — were presented to a make the set of algorithms wide like Random Forest, Decision Tree and Linear Regression flexible. In this scheme, we used RMSE Index for assessing the performance of our model which is a tool that provides both the accuracy and also acts as a metric.

Retail sales prediction Machine learning algorithms Rossman store dataset Ensemble modeling Feature selection Predictive analytics Sales forecasting Business intelligence Data-driven decision-making Retail industry insights

"RETAIL SALES PREDICTION USING MACHINE LEARING AND DEPLOYEMENT WITH AWS SAGEMAKER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.e656-e662, May-2024, Available :http://www.jetir.org/papers/JETIR2405476.pdf

"RETAIL SALES PREDICTION USING MACHINE LEARING AND DEPLOYEMENT WITH AWS SAGEMAKER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppe656-e662, May-2024, Available at : http://www.jetir.org/papers/JETIR2405476.pdf