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Predict Airbnb Prices in Seattle implementing CRISP-DM(Cross Industry Standard Process for Data Mining)

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minyansh7/CreatADataSciencePostwithCRISPDMProcess

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Creat a Data Science Post with CRISP-DM Process

  1. Project Motivation
  2. File Descriptions
  3. Result
  4. Licensing, Authors, and Acknowledgements

1. Project Motivation

For this project, I was interested in using Airbnb Seattle data to better understand:

  • What Airbnb houses are the most popular ones in market?
  • What is the factor that related with the Airbnb price the most?
  • Can we predict the price of Airbnb houses?

It is also a project for Udacity Data Scientist Nanodegree program. This project aims to have a focus on the data science process.

2. File Descriptions

listings.csv is part of Seattle Airbnb open data. It consists of various Airbnb homestay activities in Seattle area.

The dataset is accessible here:https://www.kaggle.com/airbnb/seattle/data

3. Result

Using Machine learning to predict Values of homes on Airbnb.ipynb is my full code.

Here is my blog post that summarises the project findings.

4. Licensing, Authors and Acknowledgements

Must give credit to Airbnb for the data. You can find the Licensing for the data and dexscriptive information at the Kaggle link available here.

Thanks to Kaggle and Udacity community's knowledge sharing that supports the project.

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Predict Airbnb Prices in Seattle implementing CRISP-DM(Cross Industry Standard Process for Data Mining)

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