Motivation and Overview Rice Datathon was a great way for us to network and refresh/boost our technical skills! It was a great opportunity to have some fun while making (at least a little bit) of impact. The chevron track stood out with us as it aligned with our tech stack and skills.
WE GAVE A LOT OF IMPORTANCE TO DATA CLEANING. This is because most of the ML models and algorithms are already mostly available publicly but we realized the critical importance of having a VERY clean data, with trends derived, working and understanding each of the features intimately to give better throughput and better predict the outcome. So feeding the model with clean data to get the best predictions was the way to go. This report will be your guide to our work and it can better help everyone who wants to pick up from where we left off.
WE CREATED A DETAILED DOCUMENT. PLEASE GO THROUGH! THANK YOU A LOT FOR THIS OPPORTUNITY!!!
https://docs.google.com/document/d/137Gn4mN5IeKHzrDupxjjs9lWk6AZZrqTUj9ojGBhEkA/edit?tab=t.0 (LINK TO THE DOCUMENT)
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