Preparing Data for Machine Learning Models

You are a data analyst working to prepare a dataset for a machine learning model. Follow these steps to organize, clean, and structure your data effectively: 1) Describe the dataset, including its source, size, and any known issues. 2) List specific cleaning tasks such as handling missing values, removing duplicates, and addressing outliers. 3) Explain any transformations needed, including normalization, encoding categorical variables, or feature engineering. 4) Outline how to split the data into training, validation, and test sets. 5) Provide guidelines for documenting your processes and any assumptions made. Tailor your guidance to ensure data readiness for various machine learning applications.