The problem Air Quality Index Predictor solves

The application is still in the development stage, but once it is completed it will increase the awareness among the people or society for saving the environment and care about their health. People could be able to use it to check the air quality index of their area and also once completed the project can also help by suggesting the amount of trees to be grown in the locality.

Challenges we ran into

There were many problems that we faced during the building of this project.

1. The first one was the scraping of data in which some of the columns data was not getting rendered and data was very uneven. So then we used a government website to find the data of a single column and added it to the final output.
2. The second challenge was with the hyperparameter optimization while using the Decision Tree algorithm in which we had to provide many set of values and took long time to execute.
3. The third challenge was with the integration of the model to web. We were using Jinja2 for the templating process which gave a hell lot of troubles as there were many module errors. We were actually going to add images and make it more interactive but due to Jinja2 format, we tried but were not able to add images because it was causing a lot of static errors. So from our next project we'll try not to use Jinja as templating. (P.S. We have used Jinja because we had a small bit of experience in it during college.)