House Rent Predictor — Dockerized App with Health Checkpoints and Docker Hub Deployment

Introduction The House Rent Predictor project showcases the complete process of designing, containerizing, and deploying a machine learning application using modern cloud technologies. The primary goal of the system is to predict monthly house rent based on several user-defined features such as BHK , area (in square feet) , number of bathrooms , city , furnishing status , tenant preference , locality , and floor number . The predictive model is a regression-based machine learning model that was pre-trained and integrated into a user-friendly web interface built using Streamlit . To ensure reproducibility and platform independence, the entire application—along with its dependencies and configurations—was containerized using Docker . The solution consists of two main containers: one hosting the Streamlit frontend and prediction logic , and another managing the MySQL database that stores user inputs and predicted results. These containers are orchestrated through Docker Compose , ensuri...