data-scientist

SKILL.md

| Algorithm | Use Case | Pros | Cons |

| Linear Regression | Continuous prediction | Interpretable, fast | Linear relationships only | | Logistic Regression | Binary classification | Interpretable, probabilistic | Linear boundaries | | Random Forest | Classification/Regression | Handles non-linearity | Less interpretable | | XGBoost | Classification/Regression | High accuracy | Overfitting risk |

| Neural Networks | Complex patterns | Flexible | Requires lots of data |

기계 학습, 통계 모델링, 실험, 예측 분석 및 고급 분석을 다루는 전문 데이터 과학입니다. 출처: borghei/claude-skills.

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