EstimaRent: Data Driven Rental Housing Optimisation and Market Analysis for Enhanced Decision-Making
Keywords:
Housing Market, Machine Learning, Real-Time Data, Rental Price Prediction, User-Friendly PlatformAbstract
Estimarent is a cutting-edge research programme that aims to change the housing industry by leveraging the power of machine learning. The goal of this project is to deliver very accurate rental pricing projections for specific cities via a user-friendly web platform. Estimarent provides a useful resource for those looking for rental houses by combining data from social networks like Facebook and regional WhatsApp groups. Key goals include developing expert machine learning models, specifically using LSTM for sequence data, to estimate rental charges with high precision. Property owners can optimize rental listing pricing, renters can find cheap accommodation, and real estate specialists can obtain insight into rental market dynamics. Beyond mathematics, Estimarent simplifies one of life's most important decisions: whether to rent or buy a home. As it grows, the initiative aims to revolutionise the rental housing market by providing a dynamic solution that responds to the ever-changing real estate landscape.
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