Dubai House Price Prediction using Linear Regression and Random Forest
Project Overview: This project aims to dissect the Dubai housing market through comprehensive Exploratory Data Analysis (EDA) and leverage Machine Learning algorithms to accurately predict housing prices. It combines detailed statistical analysis with advanced predictive modeling techniques to offer valuable insights into the factors influencing housing prices in Dubai.
Features: Exploratory Data Analysis (EDA): Utilizes Python libraries (Pandas, Matplotlib) for in-depth market trend analysis. Insightful Visualizations: Includes a variety of charts and graphs that highlight key market trends and prediction accuracies. Predictive Modeling: Employs algorithms like Linear Regression and Random Forest for price prediction.
Data: The dataset comprises various features affecting housing prices in Dubai, such as location, amenities, square footage, etc. Due to privacy concerns, the raw data is not included in this repository. For demonstration purposes, a sample dataset is provided.