Inspiration : We collected the data from Kaggle and generated some weather parameters from dark-sky. This way we wanted to understand the effect of weather on California Wildfire.
What it does : It gives the explanation for the fire intensity.
How we built it: We fed the generated dataset to the EazyML platform and used their features and selected best model and finally use the explanation feature of EazyML.
Challenges we ran into : To get the dark-sky data we have to get the API and then fetch the data.
Accomplishments that we're proud of: We were able to understand the weather parameters which affected most to the intensity of California Wildfire.
What we learned : We learnt the EazyML platform and it's APIs.
What's next for California_Wildfire_Intensity_Explanation : We will try to do prediction of fire intensity for the future.
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