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Hello, I'm Alina Zahra, a software developer and computer science student, and this is my very first machine learning project that I am sharing here on DevConnect. I am building my journey around software and AI development, and I hope you all like this project!
Project Summary / Overview
This project is an intelligent real estate valuation and machine learning-powered web application designed to predict property and housing prices accurately. The primary objective is to analyze historical real estate data, identify core market patterns, and compute reliable price estimates based on critical property parameters such as location, square footage, room counts, and neighborhood amenities.
Tech Stack & Tools
- Programming Language: Python
- Machine Learning & Data Science: Scikit-Learn (Random Forest), Pandas, NumPy, Pickle/Joblib
- Frontend & UI: Streamlit, Custom CSS (Glassmorphism & Gold Theme)
- Deployment & Version Control: Streamlit Community Cloud, GitHub
Key Features
Accurate Predictive Modeling: Utilizes robust regression algorithms trained on structured housing datasets to deliver precise market valuations.
Interactive User Interface: Features a clean, responsive web dashboard where users can input custom property specifications and get instant results.
Data Visualization: Displays graphs and correlation matrices to highlight how various features impact overall housing prices.
Customization & Collaboration Request
If you want this model trained on your own custom dataset, or if you want to build a complete, custom frontend website or UI for this project, feel free to reach out to me! We can discuss your specific requirements, and I can set it up, customize the backend, or build a professional frontend web application according to your exact needs.
Links & Repository
GitHub Repository: https://github.com/AlinaZahraHub/Alina-Zahra---Machine-Learning---Month-2---Task-3-Housing-Price-Prediction
Live Preview:
https://house-price-prediction--app.streamlit.app/
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