Apartment Rental Prediction in Germany by Group 2

Apartment Rental Prediction Overview

Introduction

The real estate market in Germany is a significant player in Europe, driven by the country’s robust economy and population. The project aims to bring insights about the market and help tenants make better decisions while renting appartments.

Data Sources

The analysis utilizes a comprehensive dataset sourced from reliable sources such as Kaggle and ImmoScout24 - Germany Rental Listing Portal

Methodology

The analysis employs a combination of data cleaning, exploratory data analysis (EDA), statistical modeling, and data visualization techniques to derive meaningful conclusions from the raw data.

Tools Used

The analysis was conducted using various tools and technologies, including:

• Python programming language and various libraries
• Google Colab - Jupyter Notebook
• Various Machine Learning models
• Flask app
• StreamLit

Contributors

This project was a collaborative effort. Contributors include:

• ALWIN KANNYAKONIL SCARIA
• DONA BIJU
• JERIN THENGUMPALLIL THOMAS
• MOHAMED AFTAB
• SANIKA SABEESH
• SNEHA SUJATHA

• TANVI TAKKAR