Individual skill
experiment-tracking-setup
MLflow, Weights & Biases 등 실험 추적 도구 설정, 재현성 보장, 모델 레지스트리, 실험 비교 방법론 가이드. '실험 추적', 'MLflow', 'W&B', 'Weights and Biases', '재현성', '모델 레지스트리', '실험 비교', '하이퍼파라미터 로깅' 등 ML 실험 관리 시 이 스킬을 사용한다. training-manager의 실험 관리 역량을 강화한다. 단, 모델 아키텍처 설계나 피처 엔지니어링은 이 스킬의 범위가 아니다.
ko/31-ml-experiment/.claude/skills/experiment-tracking-setup/skill.md
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# Experiment Tracking Setup — 실험 추적 및 재현성 가이드
ML 실험의 추적, 재현성 보장, 모델 버전 관리를 위한 실전 가이드.
## MLflow 설정
### 기본 구조
```python
import mlflow
mlflow.set_tracking_uri("http://localhost:5000")
mlflow.set_experiment("order-prediction")
