ml-systems

What problem does it solve?

This Skill streamlines the process of developing, validating, and deploying machine learning systems within production trading environments, ensuring reproducibility and robust controls.

Core Features & Use Cases

• Reproducible Research: Define hypotheses, build features, and estimate signal performance with clear constraints.
• Production Controls: Implement stress testing, risk controls, and diagnostics for robust deployment.
• Use Case: When developing a new trading signal, use this Skill to systematically test its performance across various market regimes, ensure it meets risk thresholds, and generate a detailed implementation memo for rollout.

Quick Start

Run python scripts/ml_systems_diagnostics.py input.csv --output diagnostics.json and keep the json artifact.