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Predicting top 5 travel destinations a new user makes his first booking

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SarveshP/Airbnb_New_User_Bookings

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Airbnb New User Bookings

How do we know which travel destination the new user books? How do you train a classifier and evaluate using a ranking metric to suggest the top 5 countries? Which countries have almost no Airbnb bookings? Do people prefer to travel long distances, do they accept different cultural languages? I answer these questions through this project.

Prerequisites

In order to run the assests you will need the following:

  • Python 3

NoteBooks

  1. Code.ipynb - Contains code for the whole analysis.
  2. Report.ipynb - A detailed report on the conducted analysis.
  3. Sessions_Features.ipynb - Construction of Features related to session data.
  4. Stats&EDA.ipynb - Contains statistical analysis and exploratory data analysis of the data.

Components

  • Data - the directory containing all the input csv files.
  • NDCG - the directory containing the description related to Normalized discounted cumulative gain(NDCG).
  • Viz - the directory containing all the vizualizations

Authors

  • Sarvesh Prattipati

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Predicting top 5 travel destinations a new user makes his first booking

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