* Basis EDA * Handling Null/Missing Values * Handling Outliers * Handling Skewness * Handling Categorical Features * Data Normalization and Scaling * Feature Engineering *Accuracy score *Confusion matrix *Classification report
A basic template for preprocessing CSV file data, including data loading, handling missing values, encoding, scaling, and splitting into training and test sets. Perfect for quick reference and consistent preprocessing in machine learning projects.
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