Airbnb-Neighborhoods-Analysis-Project

Descriptive Analysis Price Modelings Machine Leaning Visualization

Background

Airbnb has seen a dramatic growth since its inception in 2008 with the number of rentals listed on its website growing exponentially each year. Airbnb has successfully disrupted the traditional hospitality industry as more and more travelers, not just the ones who go for tourism but also business travelers who resort to Airbnb as their premier accommodation provider.

Boston, capital of Massachusetts, economic center in east coast, is a livable and beautiful city with rich history, attracting millions of tourists all over the world. Would the combination of sharing economy and tourist city create something unusual?

This project is going to dig deep into Boston Airbnb data and provide insightful suggestions to Airbnb host, customers and Airbnb. Things we did are included but not limit to data cleaning and transformation, descriptive analysis, daily price modelings (machine learning), results visualizations, review analytics (natural language processing).

1. Data Preparation

1.1 Data Cleaning and transformation

1.2 Exploratory and descriptive analysis

1.3 Feature Engineering

2. Prices Modeling

2.1 Data Splitting

2.2 Regressions (Linear, Ridge, and Lasso)

2.3 Neural Nets Regression

2.4 XGBoost Tree Model

2.5 Random Forest Model

2.7 Summary

3. Insights and Recommendations

3.1 Insights

3.2 Recommendations