Smart House Price Prediction AI – Final Year Python Project with ML & Flask
A cutting-edge Python ML project for house price prediction using Flask & scikit-learn — ideal for final year students. Get source code, setup guide, explanation, and report starting at just ₹99!
Technology Used
Python | Flask | scikit-learn | joblib | HTML5 | CSS3 | JavaScript | Plotly.js | Pandas | NumPy | Flexbox | Font Awesome
Project Files
Overview
The House Price Prediction AI is a full-stack web application that leverages machine learning (ML) to predict residential property prices based on multiple input features like lot area, year built, quality, garage type, and more. Built using Python, Flask, and scikit-learn, this project is perfect for students looking for unique final year projects that stand out in placements and academics.
Key Features
- Advanced ML Model: Trained using Random Forest Regressor and Gradient Boosting for high accuracy.
- Interactive Web Interface: Built with HTML, CSS, and JavaScript for seamless user experience.
- Real-Time Predictions: Instant price estimation after form submission.
- Data Visualization: Integrated Plotly.js charts showing feature importance and price trends.
- Responsive Design: Works flawlessly on mobile, tablet, and desktop.
- Model Persistence: Pre-trained model saved using joblib for fast deployment.
- User-Friendly Input Form: Sliders and dropdowns for easy data entry.
Applications & Use Cases
This project is ideal for:
- Final year college projects in Computer Science, IT, or Data Science.
- Real estate startups looking for price estimation tools.
- Learning end-to-end machine learning pipeline development.
- Understanding model deployment using Flask API.
- Gaining hands-on experience in data preprocessing, feature engineering, and model evaluation.
Technology Stack
Backend: Python, Flask
Machine Learning: scikit-learn, pandas, numpy, joblib
Frontend: HTML5, CSS3, JavaScript, Plotly.js
UI/UX: Flexbox, Grid, Font Awesome Icons
Deployment: Local Server (Flask), Ready for Cloud (Heroku, Render)
What You Get?
When you purchase this project from CodeAJ Marketplace, you can choose from:
- Complete Source Code (₹99 onwards)
- Project Setup Assistance (+₹199)
- Detailed Source Code Explanation (+₹299)
- Ready-to-Submit Project Report (PPT + PDF) (+₹399)
Combine options and get a complete final year project package — presentation, code, report, and support!
Frequently Asked Questions
Extra Add-Ons Available – Elevate Your Project
Add any of these professional upgrades to save time and impress your evaluators.
Project Setup
We'll install and configure the project on your PC via remote session (Google Meet, Zoom, or AnyDesk).
Source Code Explanation
1-hour live session to explain logic, flow, database design, and key features.
Want to know exactly how the setup works? Review our detailed step-by-step process before scheduling your session.
₹999
Custom Documents (College-Tailored)
- Custom Project Report: ₹1,500
- Custom Research Paper: ₹1,000
- Custom PPT: ₹800
Fully customized to match your college format, guidelines, and submission standards.
Project Modification
Need feature changes, UI updates, or new features added?
Charges vary based on complexity.
We'll review your request and provide a clear quote before starting work.
