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This skill builds and executes automated pipelines to clean, validate, and transform data for machine learning, covering ETL workflows, error handling, and quality reporting so Claude can deliver analysis-ready datasets.

Ray Data is a scalable distributed data processing library for ML workloads, streaming execution across CPU/GPU, integrates with Ray Train, PyTorch, TensorFlow, and handles Parquet/CSV/JSON/images for preprocessing, ETL, or batch inference from single node to cluster.

Automates clustering workflows on supplied datasets with K-means, DBSCAN, or hierarchical algorithms, handling preprocessing, validation, metrics, and visualizations to expose groupings and anomalies.

FlowIO reads and writes Flow Cytometry Standard (FCS) files, exposing metadata, channels, and NumPy event arrays while allowing CSV/DataFrame conversion, making it ideal for cytometry pipelines and backend preprocessing services.

PathML is a Python toolkit for computational pathology workflows, loading 160+ slide formats, preprocessing H&E images, constructing spatial graphs, training HoVer-Net/HACTNet models, and analyzing multiplex imaging for ML-ready pathology data.

Comprehensive guidance for building classical machine learning workflows with scikit-learn, spanning supervised and unsupervised algorithms, preprocessing, evaluation, tuning, and production-ready pipelines for structured or text data.