The primary goal of this project is to explore and develop AI-driven solutions that enhance decision-making in real estate investing. The project will focus on leveraging machine learning models, predictive analytics, and data-driven insights to assess property values, market trends, and investment risks. More details :

Understanding AI in Real Estate:

• Research how AI is currently used in the real estate sector.
• Identify key areas where AI can enhance investment decisions (e.g., price prediction, risk assessment, rental yield estimation).

Data Collection and Preprocessing:

• Gather real estate data from public sources (e.g., property listings, market reports, rental trends, economic indicators).
• Clean and preprocess data for AI model training.

Building AI Models:

• Implement machine learning algorithms (e.g., regression, classification, clustering) to predict property prices and investment potential.
• Train models using historical real estate data.

Market Trend Analysis and Risk Prediction:

• Use AI-driven sentiment analysis on real estate news and market reports.
• Develop models to assess the risk factors of real estate investments.

Deployment and Visualization:

• Develop a dashboard or web application to present AI-generated insights.
• Implement interactive features for real estate investors to test different scenarios.

• A research report on AI applications in real estate investing.
• A cleaned and preprocessed real estate dataset.
• AI models predicting property prices and risk factors.
• A web-based or dashboard visualization tool for real estate insights.
• A final presentation or report summarizing findings and model performance.
• Create a video of the prototype