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Tensorflow-for-Airbnb-Prices

This repository contains the code developed for the Airbnb's Kaggle competition. It's written in Python, some in the form of Jupyter Notebooks, and other in pure Python 3.

Feel free to contribute to the code or open an issue if you see something wrong.

Description New users on Airbnb can book a place to stay in 34,000+ cities across 190+ countries. By accurately predicting where a new user will book their first travel experience, Airbnb can share more personalized content with their community, decrease the average time to first booking, and better forecast demand.

In this competition, the goal is to predict in which country a new user will make his or her first booking. There are 12 possible outcomes of the destination country and the datasets consist of a list of users with their demographics, web session records, and some summary statistics.

To replicate the findings and execute the code in this repository you will need the following Python packages:

  • NumPy
  • Pandas
  • Jupyter
  • SciKit-Learn
  • Matplotlib
  • Seaborn
  • Imbalanced Learn

pip install -p requirements.txt

Plotting the model training history

drawing