automl-pipeline-setup
Эксперт AutoML. Используй для automated machine learning, hyperparameter tuning и model selection.
npx skills add majiayu000/claude-skill-registry --skill automl-pipeline-setup-dengineproblem-agents-monorepo --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# AutoML Pipeline Setup Expert Эксперт по проектированию и реализации автоматизированных систем машинного обучения. ## Архитектура пайплайна ### Модульные компоненты ``` Data Ingestion → Validation → Feature Engineering → Model Training → Evaluation → Deployment ``` ### Конфигурация через YAML ```yaml pipeline: name: customer_churn_prediction version: "1.0" data: source: "s3://bucket/data.parquet" validation: null_threshold: 0.1 duplicate_check: true features: numerical: - age - tenure - monthly_charges categorical: - contract_type - payment_method target: churn automl: framework: h2o max_runtime_secs: 3600 max_models: 20 stopping_metric: AUC sort_metric: AUC deployment: platform: mlflow model_registry: true ``` ## Data Validation с Great Expectations ```python import great_expectations as gx def validate_data(df, expectation_suite_name="default"): context = gx.get_context() # Создание expectation suite suite = context.add_expectation_suite(expectation_suite_name) # Определение expectations validator = context.get_validator( batch_request=batch_request, expectation_suite_name=expectation_suite_name ) # Проверки качества данных validator.expect_column_values_to_not_be_null("customer
- Архитектура пайплайна
- Модульные компоненты
- Конфигурация через YAML
- Data Validation с Great Expectations
- Feature Engineering Pipeline
- H2O AutoML
- MLflow Experiment Tracking
- Optuna для Hyperparameter Tuning
- Airflow DAG для оркестрации
- Рекомендации по фреймворкам
- Лучшие практики
What does the automl-pipeline-setup skill do?
Эксперт AutoML. Используй для automated machine learning, hyperparameter tuning и model selection.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill automl-pipeline-setup-dengineproblem-agents-monorepo --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.