1. Project Overview
1.1 Introduction
This is a capstone project for the Udacity data science nanodegree program.
In this project, I analyze demographics data for customers of a mail-order sales company in Germany, comparing it against demographics information for the general population. I use unsupervised learning techniques to perform customer segmentation, identifying the parts of the population that best describe the core customer base of the company. Then, I use a supervised model to predict which individuals are most likely to convert into becoming customers for the company.
1.2 Data sets
The data is provided by Bertelsmann Arvato Analytics and represents a real-life data science task. …
Note:
This is the second version of this notebook. In this version, I
- add more analysis, such as the top 10 neighbourhoods with the most listings and the top 10 most and least expensive neighbourhoods in Manhattan and Brooklyn, in the data exploratory analysis section.
- add Ridge Regression, Lasso Regression, grid search, and feature importance study in the data modeling section.
- update code and add some other discussions.
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1. Introduction
Airbnb has…
