• Objective: Developed a web-based application to predict house prices using the Ames Housing dataset. • Technologies Used: Python, Flask, Scikit-learn, Pandas, NumPy, Matplotlib,HTML,CSS, Javascript • Key Features: • Implemented a machine learning model to predict house prices based on various features of the Ames Housing dataset. • Designed an HTML form to collect user input, which is then converted into a JSON object for the model to process. • Added a feature to auto-fill the form with random data from the dataset for quick testing. • Integrated the application into a serverless environment, optimizing it for deployment and scalability.