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What is this Python project?

This Python project is a comprehensive machine learning utility package designed to simplify the workflow of data preprocessing, feature engineering, model training, evaluation, and visualization. Its main features include:

• Automated Data Cleaning: Handles missing values, outliers, and inconsistent data formats.
• Feature Engineering: Generates new features, encodes categorical variables, and scales numeric data automatically.
• Model Training & Evaluation: Supports multiple ML algorithms for classification and regression, with built-in metrics and cross-validation.
• Visualization: Generates correlation heatmaps, feature importance plots, and performance graphs to help interpret models.
• Artifact Management: Saves trained models, plots, and reports as PNGs or files for easy sharing and documentation.
• Fast Mode: Optional quick training mode for rapid prototyping of models.

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What's the difference between this Python project and similar ones?

Unlike other ML utility packages, this project offers:

1. End-to-End Workflow: Combines data cleaning, feature engineering, model training, evaluation, and visualization in a single package.
2. User-Friendly Output: Automatically generates plots and reports that are ready to present, reducing the need for manual coding.
3. Flexible Model Support: Supports both classic ML algorithms and advanced models, with easy configuration.
4. Customizable Pipelines: Users can tweak preprocessing and feature engineering steps according to their dataset.
5. Lightweight & Fast: Optimized for small to medium datasets while maintaining clarity in outputs.
6. Artifact Handling: Stores outputs systematically, so users can track model performance over time.

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