Built a machine learning model using the UCI Adult dataset to predict whether an individual earns more than $50K annually based on features like age, education, occupation, and work hours. The model was trained using a Random Forest Classifier with label encoding and evaluated using accuracy and classification metrics. All preprocessing and training were done in Google Colab. The final model was deployed as an interactive web app using Streamlit, allowing real-time user input and predictions. The project is hosted on GitHub and publicly accessible via Streamlit Cloud.