a maximalist but larp-friendly intro to supervised machine learning by a maxxed out noob

• follows a basic classification problem
• settles on and 'tracks' a logistic regression model
• covers all the 'talking points'; problem formulation, EDA, preprocessing, model selection, training, evaluation, metrics, tuning, classification report, error analysis, interpretation, possible improvement, deplyoment*
• a learning experience of oat (odongonocap ?)
• you can genuinely feel the larp