This GitHub project involves a Streamlit web application for predicting the difficulty level of recipes and recommending similar ones. It uses a hybrid ensemble machine learning model that combines multiple algorithms to analyze recipe features, such as ingredients and cooking steps, and provides tailored suggestions. The system leverages data on user preferences and cooking experience to offer personalized recipe recommendations and estimate how challenging a dish may be.