According to Yelp, "Elite-worthiness is based on a number of things, including well-written
reviews, high quality tips, a detailed personal profile, an active voting and complimenting record,
and a history of playing well with others." Unfortunately, Yelp does not explicitly state eligibility
nor requirements to be an Elite user. Users can only self-nominate and hope for the best. Given Yelp's
user dataset, can we leverage machine learning to determine Yelp's Eliteness criteria?
LendingClub is a peer-to-peer lending company, offering loans with fixed interest rates and equal payments.
Each loan is broken up into many Notes, which corresponds to a fraction of the overall loan. Investors
seeking higher yield fixed-income securities can build their portfolio by purchasing/investing in many Notes
from different loans and borrowers. Can we maximize returns by building an investment model that predicts loan
status, whether a loan will be fully paid or default?
