Detalle del Skill
machine learning
Broad Python ML coverage from training through MLOps.
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SKILL.md
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--- name: Machine Learning description: Python machine learning with scikit-learn, PyTorch, and TensorFlow version: "2.1.0" sasmp_version: "1.3.0" bonded_agent: 03-data-science bond_type: PRIMARY_BOND # Skill Configuration retry_strategy: exponential_backoff observability: logging: true metrics: model_accuracy --- # Python Machine Learning Skill ## Overview Build machine learning models using Python libraries including scikit-learn, PyTorch, and supporting tools. ## Topics Covered ### Scikit-learn - Data preprocessing - Model selection - Training pipelines - Cross-validation - Hyperparameter tuning ### PyTorch Basics - Tensor operations - Neural network modules - Training loops - DataLoader usage - GPU acceleration ### Feature Engineering - Feature selection - Dimensionality reduction - Feature scaling - Encoding techniques - Missing data handling ### Model Evaluation - Metrics selection - Confusion matrix - ROC curves - Learning curves - Model comparison ### MLOps Basics - Model serialization - Experiment tracking (MLflow) - Model versioning - Serving models - Reproducibility ## Prerequisites - Python fundamentals - NumPy and Pandas - Statistics basics ## Learning Outcomes - Train ML models - Evaluate model performance - Build ML pipelines - Deploy models to productionLeer la fuente completa en GitHub (abre una página externa)