yaqoobd/germany-rental-housing-prediction

Germany is facing a housing crisis with various causes, including population growth and slow construction. The government aims to build 50,000 more units and create a new ministry to oversee the issue. Data cleaning, visualization, and feature engineering were used to predict house costs and compare models.

Germany Rental Housing Prediction 🏘️📈

Introduction 🌟

• Housing Crisis in germany is getting grave.
• The country’s current government wants to create an entirely new ministry to oversee it.
• Government pledge is to built 50,000 more units than the current goal.
• Berlin tried to cap rents for five years, but court threw out the law earlier last year.
• Germany has 1.8 million empty apartments, according to the DStGB, outside cities where people are less interested in living.
• Population growth, bad decisions, slow construction, competing demands: These are just some of the causes of Germany's housing crisis

Dataset 📊

• The data is obtained from “Kaggle” for this project.
• The data was scraped from Immoscout24.
• The data set contains most of the important properties, such as living area size, the rent etc.
• The dataset has 49 Columns and 268850 Rows.
• Data could be found at https://www.kaggle.com/corrieaar/apartment-rental-offers-in-germany

What to Expect 🎯

• Data cleaning to clear the outliers and remove columns that doesn't have high correlation to the prediction
• Create visualization to have a better understanding of the rental properties in Germany.
• Try to Answer some pressing questions.
• Feature engineering from the original variable to create a better model
• Create a tool that estimate the house cost predicted by many variables
• Compare those model to see the best results.

[Yaqoobdavid_Rental _Prediction_presentation_Original.pptx] (https://github.com/YaqoobD/Germany-Rental-Housing-prediction/files/8597611/Yaqoobdavid_Rental._Prediction_presentation_Original.pptx)