🏡 Real Estate Data Analysis & Prediction

📌 Project Overview

This project focuses on analyzing real estate sales data to extract meaningful market insights and build predictive models for property prices. The goal is to create a structured dataset from raw real estate data, visualize trends using Tableau, and apply machine learning models to predict future prices.

🔍 Key Features

• Data Collection & Cleaning: Processed and structured real estate data for analysis.
• Exploratory Data Analysis (EDA): Identified pricing trends, demand patterns, and suburb-wise distributions.
• Visualization & Dashboarding: Created interactive Tableau dashboards to display market insights.
• Machine Learning Predictions: Trained models to forecast property prices based on historical data.

🛠 Technologies Used/to be used

• ✅ R (Tidyverse, Rvest, Lubridate) → Data collection, cleaning, and transformation.
• ✅ Tableau → Creating dashboards and visual reports.
• ✅ Python (Scikit-learn, XGBoost, Random Forest) → Building predictive models.