Inspiration
A food delivery company has to deal with a lot of perishable raw materials. Thus it is very important for such a company to accurately forecast daily and weekly demand. We have seen the problem of unbalanced demand and supply in food delivery industry. We always wanted to solve this problem, so this our chance to represent our idea and solution
What it does
We created website using an appropriate machine learning model, to forecast number of orders to gather raw materials for next few weeks. The prediction model is a generalized model which means other companies or services can rebuild this model according to their data. In the web application, a separate section called ‘inventory management’ is for restaurants where they can log in/sign up and can keep record of available inventory and also manage their customers and orders.
How we built it
Machine learning model is built using gradient boost regressor model. Inventory management's backend is built using python web framework django and frontend using HTML, CSS and bootstrap.
Challenges we ran into
We faced challenge while building ML model but we tune it more and achieved better accuracy at the end.
Accomplishments that we're proud of
We feel that we have taken the first step to solve a major real world problem.
What we learned
The biggest lesson we learned is to complete the whole project in such a short time with amazing teamwork.
What's next for Food demand forecasting and Inventory management
We can keep improving model by feeding it more data and also add more features in inventory management
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