ce-classification

Early Stopping Callback - Auto-activating skill for ML Training.

Comprehensive ML model evaluation with multiple metrics, cross-validation, and statistical testing.

Train ML models with scikit-learn, PyTorch, TensorFlow.

Scikit-learn model training skill with cross-validation, hyperparameter tuning, pipeline construction, and model serialization.

Handle CE classification workflows for binary and multiclass prediction semantics and class-focused explanation behavior.

Master SOTA data prep for Kaggle comps: automated EDA (Sweetviz), cleaning (Pyjanitor), and feature selection (Polars + XGBoost) for medium datasets…

Generates data cleaning pipelines for pandas/polars with handling for missing values, duplicates, outliers, type conversions, and data validation.

Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis.

Master training pipelines - orchestration, distributed training, hyperparameter tuning

Master machine learning foundations - algorithms, preprocessing, feature engineering, and evaluation

Autonomous LLM training optimization with GPU support.

XGBoost gradient boosting library.