  One of the first things to do while planning a trip is to book a good place
to stay. Booking a hotel online can be an overwhelming task with thousands of
hotels to choose from, for every destination. Motivated by the importance of
these situations, we decided to work on the task of recommending hotels to
users. We used Expedia's hotel recommendation dataset, which has a variety of
features that helped us achieve a deep understanding of the process that makes
a user choose certain hotels over others. The aim of this hotel recommendation
task is to predict and recommend five hotel clusters to a user that he/she is
more likely to book given hundred distinct clusters.
