lqf_machine_learning_expert_guide

# LQF Machine Learning Expert Guide ## When to Use This Skill Use this skill when: - Building ML models (classification, regression, clustering, forecasting) - Evaluating model performance and debugging issues - Feature engineering and data preprocessing for ML - Hyperparameter tuning and model optimization - Debugging overfitting, underfitting, or poor generalization - Choosing between traditional ML and deep learning approaches - Establishing baselines and conducting ablation studies - Performing error analysis and model validation - Statistical modeling with predictive components ## Not For / Boundaries **Out of Scope:** - Pure data visualization without modeling (use data visualization skills) - Database queries without predictive modeling - Basic descriptive statistics without ML context - Production deployment infrastructure (use MLOps/deployment skills) - Reinforcement learning (specialized domain) - Time series forecasting with specialized methods (use time series skills) **Required Inputs - Ask User If Missing:** 1. What is the problem type? (classification, regression, clustering, etc.) 2. What does your data look like? (size, number of features, target variable distribution) 3. Have you established a baseline yet? (dummy predictor, simple heuristic) ## Critical Discussion Protocol This skill operates in **Critical Engagement Mode** - every proposal (user's or your own) undergoes systematic critique and iterative refinement. ### Core Principles 1. **No Firs...