Data & Analytics · By wshobson

Covers portfolio risk measurement with VaR, CVaR, Sharpe, Sortino and drawdown, plus guidance on limits, stress tests and tail risk.

wshobson/agents

Builds trustworthy trading backtests by guarding against look-ahead and survivorship bias, overfitting and ignored costs, with walk-forward analysis.

wshobson/agents

Sets up data quality checks with Great Expectations, dbt tests and data contracts, with checkpoints and pass-fail reports for pipelines.

wshobson/agents

Guides an agent through designing an MLOps pipeline that covers data preparation, training, validation and deployment, with DAG orchestration and reference guides.

wshobson/agents

Patterns for writing production-ready Apache Airflow DAGs: task dependencies, custom operators and sensors, local testing, and rules for what to avoid.

wshobson/agents

Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies.

wshobson/agents

Speed up slow Apache Spark jobs by tuning partitions, shuffles, data skew, caching and executor memory, with do and don't rules for PySpark code.

wshobson/agents

Python error handling patterns including input validation, exception hierarchies, and partial failure handling.

wshobson/agents