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Machine Learning / AI Intermediate

House Price Prediction System

A real estate valuation tool that predicts residential property prices in Bengaluru using Linear Regression trained on 13,320 actual property listings. Extensive data cleaning and domain-knowledge outlier removal improves model R² from 0.63 to 0.845.

Tech Stack: Python, Linear Regression, Scikit-learn, Flask, Pandas, Feature Engineering, Real Estate Downloads: 99

What's Included in Your Download

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Source Code

Complete working codebase with clean folder structure & dependencies

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Project Report

Editable report customized with your name, college & guide details

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Presentation Deck

Professional PPT slides ready for college project viva presentations

Viva Questions Prep

10 detailed technical Viva Q&As with multi-paragraph explanations

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Architecture Diagram

System workflow flowchart & data processing pipeline specs

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Academic Synopsis

University-standard 1-page project synopsis for pre-approval

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Setup & Run Guide

Step-by-step installation, environment setup & execution instructions

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Completion Certificate

Official ProjectHub certificate of completion personalized with your name

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100% Customizable — Make It Your Own
The report, PPT slides, and source code are fully editable. Change the title page, add your college name, modify sections, rename variables, extend features — anything your college or guide requires. No restrictions whatsoever. The pre-trained model is bundled inside — no training from scratch required.

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Viva Questions & Answers

Prepare for your project viva with these likely questions and suggested answers.

1. What is the core objective of the House Price Prediction System and what real-world problem does it solve?
2. Explain the system architecture and end-to-end data flow in House Price Prediction System.
3. Why was Python, Linear Regression, Scikit-learn, Flask, Pandas, Feature Engineering, Real Estate selected for this project over alternative frameworks?
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📐 System Architecture & Workflow

High-level architectural flowchart of the data flow and system modules.

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📄 Academic Synopsis (University Standard)

Pre-formatted 1-page project synopsis ready for college submission.

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ACADEMIC PROJECT SYNOPSIS...
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1. PROJECT TITLE:
[Hidden content]

2. DOMAIN & FIELD:
[Hidden content]
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💼 LinkedIn Project Launch Post

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🚀 Excited to announce the successful completion of my major project!

As part of my Engineering curriculum...

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Add This to Your Resume

Copy-ready resume bullet points are included with this project.

• Engineered and deployed the House Price Prediction System, providing a robust solution for machine learning / ai challenges.

• Utilized a modern technology stack including Python, Linear Regression, Scikit-learn, Flask, Pandas, Feature Engineering, Real Estate to build a highly scalable, secure, and modular application architecture.

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