Design an End-to-End Housing Price Prediction Machine Learning System

Predictive modeling is a critical skill for data scientists, widely used across various industries. In real estate, predictive analytics and valuation modeling are gaining momentum, with both startups and established companies increasingly adopting data-driven approaches to forecast housing prices.  

In this Build Project, you will retrieve, clean, and preprocess real-world housing data, transforming it into a format suitable for machine learning. You will explore and visualize the data to gain insights, then apply supervised learning algorithms to predict the sales price for each house. Throughout the project, you'll focus on optimizing model performance through feature selection and hyperparameter tuning. Additionally, you'll deploy your final model using AWS SageMaker, making it accessible via cloud infrastructure. This hands-on project will not only enhance your predictive modeling skills but also give you practical experience in cloud-based machine learning deployment.