engineering-ml-features
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data-engineering-storage-remote-access-libraries-obstore
High-performance Rust-based remote filesystem library. Covers store creation, basic operations, async API, streaming uploads, Arrow integration, and fsspec compatibility wrapper.
4data-engineering-observability
Observability and monitoring for data pipelines using OpenTelemetry (traces) and Prometheus (metrics). Covers instrumentation, dashboards, and alerting.
4data-engineering-storage-formats
Modern data serialization formats: Parquet, Apache Arrow (Feather/IPC), Lance (ML-native), Zarr (chunked arrays), Avro, and ORC. Covers compression, partitioning, and format selection.
4data-science-visualization
Data visualization for Python: Matplotlib, Seaborn, Plotly, Altair, hvPlot/HoloViz, and Bokeh. Use when creating exploratory charts, interactive dashboards, publication-quality figures, or choosing the right library for your data and audience.
2working-in-notebooks
Use for Jupyter, JupyterLab, marimo, and Google Colab workflows. Choose this skill when creating, converting, or improving reproducible notebooks for data exploration, analysis, documentation, or teaching.
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