Predict the severity of airplane crash

Flying has been the go-to mode of travel for years now; it is time-saving, affordable, and extremely convenient. According to the FAA, 2,781,971 passengers fly every day in the US, as in June 2019. Passengers reckon that flying is very safe, considering strict inspections are conducted and security measures are taken to avoid and/or mitigate any mishappenings. However, there remain a few chances of unfortunate incidents. Imagine you have been hired by a leading airline. You are required to build Machine Learning models to anticipate and classify the severity of any airplane accident based on past incidents. With this, all airlines, even the entire aviation industry, can predict the severity of airplane accidents caused due to various factors and, correspondingly, have a plan of action to minimize the risk associated with them.

The dataset comprises 3 files:

1. Train.csv: [10000 x 12 excluding the headers] contains Training data.
2. Test.csv: [2500 x 11 excluding the headers] contains Test data.
3. sample_submission.csv: contains a sample of the format in which the Results.csv needs to be.