Inventory management is an essential aspect of any business that deals with the production and distribution of goods. It involves the careful monitoring and control of the quantity and location of products to ensure efficient operations and customer satisfaction. One of the most significant challenges that businesses face in inventory management is determining the optimal level of inventory to meet customer demand while minimizing inventory costs. Inventory demand forecasting is the process of predicting future customer demand for products or goods, and it plays a critical role in inventory management.
This project aims in predicting the quantity of a certain product in advance primarily. The model used will be XG Boost since it provides optimum results. It will use the given dataset to train itself and then will be able to predict the quantity of products required for the next 60 days. On the basis of the predicted quantities, it will also be able to show a list of the trending products in the next 60 days. With the help of this, any layman that does not understand graphs and values, will still be able to figure out what needs to be stocked more and for which product the stock has to be reduced. The user can download the report which contains the overview uploaded dataset,predictions for next 60 days and predicted quantity graph of every product.
Home Page
Upload Dataset
View Uploaded dataset
View Predictions
View actual sales graph of selected product
View predicted sales graph of selected product
Generate Report
Generated Report
- Aaman Bhowmick
- Nandana Nair
- Sakshi Patil
- Prajwal Patil