Build a complete end-to-end machine learning project using my dataset (CSV). Include all main ML steps — from data loading to model deployment — with a Streamlit web UI. Requirements: Data Loading & EDA Load and preview dataset. Show missing values, distributions, correlations, and basic visualizations. Data Preprocessing Handle missing data, encode categorical columns, scale numeric features, and remove outliers. Allow feature selection. Model Training Train and compare multiple algorithms: Use cross-validation and hyperparameter tuning. Model Explainability Streamlit UI Upload dataset, select target, preprocessing, and models. Show EDA visuals, model results, and make predictions. Option to download model and pipeline. Deliverables Streamlit app (app.py), clean scripts, saved model, requirements.txt, and README.md.