🏠 Airbnb Berlin - Machine Learning Analysis

A machine learning project analyzing Airbnb listings in Berlin using Classification and Clustering techniques.

📊 Project Overview

Task	Algorithm	Objective
Classification	KNN, Random Forest	Predict room_type of listings
Clustering	K-Means	Segment listings by price patterns

🛠️ Tech Stack

📁 Project Structure

Machine-Learning-Final-Project/
├── Classification.ipynb       # KNN & Random Forest models
├── Clustering.ipynb          # K-Means clustering analysis
├── air_bnb.csv              # Original dataset
├── Machine Learning Report.pdf
└── Machine Learning Airbnb Presentation.pdf

🔬 Experiments

Classification

• Goal: Predict room type (Entire home, Private room, Shared room)
• Models: K-Nearest Neighbors, Random Forest
• Features: Price, minimum nights, reviews, availability

Clustering

• Goal: Discover natural groupings in listings
• Analysis:
  • Price vs Number of Reviews
  • Price vs Minimum Nights

🚀 Usage

# Open Jupyter notebooks
jupyter notebook Classification.ipynb
jupyter notebook Clustering.ipynb

📈 Results

See the full analysis in the included PDF reports.

📝 License

MIT