ml-analysis

What problem does it solve?

Automates end-to-end ML analysis from raw data to evaluated models.

Core Features & Use Cases

• Performs data understanding and profiling (EDA) before modeling.
• Builds robust preprocessing pipelines (imputation, encoding, scaling) with leakage prevention and reproducibility.
• Trains baseline and main models, supports AutoML guidance, and generates full evaluation reports.
• Example: build a churn/prediction model on tabular data with feature engineering and model comparison.

Quick Start

Provide the dataset path and an optional target column, and the skill will execute the full ML pipeline from EDA through feature engineering and model evaluation to a final report.