DilliWhether

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  MODEL PREDICTS

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Inspiration

The DELHI NCR Region is one of the most populated regions of India. So the amount of pollution increases gradually too. A good understanding of weather conditions could help you to choose the right transport medium to travel thus saving your time an also beneficiary to your health.

What it does

DilliWhether takes some inputs from the user about the weather conditions outside and suggests the most suitable mode of travelling by using RandomForestRegression . It also provides recent news about the region weather conditions and other charts and stats.

How we built it

Built with streamlit, sklearn , dataset from kaggle

Challenges we ran into

Model was not uploading to Github so I had to push it through git lfs. Filtering the dataset took more time than expected.

Accomplishments that we're proud of

Giving best results to the user is the greatest accomplishment.

What we learned

Learned new technology to upload large files on github through GIT LFS. Learned how to use RandomForest and streamlit to give productive results.

What's next for DilliWhether

Will integrate Google Maps api and also text messages could be sent through*Twilio* api to gather more data and provide better results.

Built With

• kaggle
• machine-learning
• python
• streamlit