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Machine Learning - Model Deployment Demo

This repo contains the boilerplate code to be used for a demo on model deployment, using the classic Titanic dataset (loaded via seaborn) to predict passenger survival.

The demo includes a very basic EDA and intentionally skips advanced preprocessing, feature engineering, hyperparameter tuning, and cross-validation to keep the focus on project structure.

The demo includes a very basic EDA and intentionally skips advanced preprocessing, feature engineering, hyperparameter tuning, and model validation (using a train/validation/test split or cross-validation) to keep the focus on project structure.

The goal is to demonstrate code organization and common patterns, not to build a perfect model.

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