A comprehensive toolkit of prompts designed to guide you through advanced stages of machine learning model development, from selection and tuning to feature engineering and deployment.
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Generate a comprehensive blueprint for feature engineering, outlining steps to transform raw data into optimal features for machine learning models.
Formulate a detailed strategy for hyperparameter tuning to optimize machine learning model performance efficiently.
Recommend and justify the optimal machine learning model for a given dataset and problem, considering various constraints and performance metrics.
Develop a comprehensive plan for deploying a machine learning model into a production environment, including testing, infrastructure, and monitoring.
