Mumbai House Price Prediction using Regression and Deep Learning
This paper presents a predictive modelling study of house prices in Mumbai, India, using regression analysis and deep learning. Housing prices in Mumbai vary widely with location, carpet area, number of bedrooms, amenities and property age, which makes accurate estimation difficult for buyers, sellers and analysts. Several regression models were built and compared with a deep learning (neural network) model. The final model was deployed as an interactive web application built with Streamlit, so users can enter property details and get an estimated price. The paper covers data preparation, model development, evaluation, deployment and limitations. Live app: https://mumbai-house-price-predictor-nz5imvmojpkrmqze94by86.streamlit.app/Source code: https://github.com/Someshshetty/mumbai-house-price-predictor The dataset used is sample data created for academic purposes, so results demonstrate the methodology and are not real market valuations.
Authors
- Somesh Shetty
Institutions
- R A Podar College of Commerce and Economics (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-29
- DOI
- https://doi.org/10.5281/zenodo.23037669
- Primary Topic
- Housing Market and Economics
- Type
- preprint