I have a raw set of patient records and want to turn it into a functional medicine-recommendation engine built in Python. The system should read symptom text typed by a user, run it through a pre-trained machine-learning model, and return a ranked list of suitable medications. Scope and key tasks • Data pipeline: remove duplicate records and normalise numeric or categorical values so every observation is model-ready. • Feature selection & training: experiment with at least Random Forest and Logistic Regression; pick the best model using accuracy, precision and recall. • Evaluation report: include confusion matrices and a short note explaining why the chosen model performs best. • Lightweight dashboard: a simple Flask or Streamlit interface with one free-text field for symptoms and a results pane listing the suggested medicines. • Clean, well-commented code plus a README describing setup, usage and how to extend the model with medical history or allergy data later. Everything should run end-to-end on my local machine with clear install instructions (virtualenv or conda).