We all saw what COVID-19 did to our lives in these two years. It was the worst for the people with no resources. So, it is our wish to help the ones who have lost a lot. Through this web application, we hope we can bring a small speck of change.

What it does

It is a Machine Learning model, which is trained by a dataset which comprises of current trend of sales in the retail market. Through this model, the user can predict the profits based on the current trend for a product of their choice with a desired quantity.

How we built it

We trained the model using pandas (python), then we used flask as the backend language to implement the model and finally we used Heroku to deploy our final model. We also used HTML, CSS and JavaScript to design our web application pages. We also implemented Firebase authentication services to keep a note on who visits our page and security.

Challenges we ran into

It was our first time deploying a live project using Heroku so we had to face some hurdles in our way. But we finally managed to make it work.

Accomplishments that we're proud of

We didn't expect to make such good pages and we learnt a lot from this hackathon. So we feel proud that we learnt something new and created a working project.

What we learned

We learned how to deploy a model using Heroku. We also learned about Flask, some new attributes in CSS and functions in JavaScript.

What's next for Retail Solutions and Advices

Even if we don't make it to the finals, we will continue to work more efficiently to improve our product. We are thinking to increase our scope to use Machine Learning models to help the other sectors of the society. And we soon might be All Solutions and Advices.

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