Sales forecasting is an essential task for the management of a store. Being able to estimate the number of products that a retail store is going to sell in the future will allow the owners of these shops to prepare the inventory that they will need.

In this project, we are building a system that analyses the previous trends of sales which includes sales on various days and predicts future sales. The goal of this project is to forecast the sales of stores by using time series analysis. Here time series analysis algorithms such as RNN (Recurrent Neural Network) & LSTM (Long Term Short Memory) are used to analyze the past trends of sales of stores. Create and deploy flask-based web Application and integrate AI model to it.

The objective of the project is to build a web application where the user gives the last ten days' sales values and gets the prediction for the 11 th day which is showcased on UI.

Technical Architecture: