Implements Change Data Capture patterns for real-time data integration
原文の言語: 英語
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このリポジトリの skills
SkillsMP は a5c-ai/babysitter から 2,079 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
a5c-ai/babysitter収集済み skill 2,079 件中 40 件を表示しています。
Implements Change Data Capture patterns for real-time data integration
原文の言語: 英語
Analyzes and optimizes costs for cloud data platforms
原文の言語: 英語
Enriches data catalog entries with automated metadata
原文の言語: 英語
Extracts and maps data lineage from various sources including SQL, dbt, Airflow, and Spark, generating comprehensive lineage graphs for impact analysis.
原文の言語: 英語
Profiles data assets to assess quality dimensions, detect anomalies, and generate comprehensive data quality reports with actionable recommendations.
原文の言語: 英語
Analyzes dbt projects for best practices, performance, maintainability, and generates actionable recommendations for improvement.
原文の言語: 英語
Validates dimensional models against Kimball methodology best practices
原文の言語: 英語
Optimizes feature engineering pipelines and feature store configurations
原文の言語: 英語
Generates Great Expectations suites from data profiles and business rules
原文の言語: 英語
Selects and configures optimal incremental model strategies
原文の言語: 英語
Designs and optimizes Apache Kafka topics and configurations
原文の言語: 英語
Designs and optimizes One Big Table (OBT) patterns
原文の言語: 英語
Generates Slowly Changing Dimension implementations across platforms
原文の言語: 英語
Manages schema evolution and compatibility across data systems
原文の言語: 英語
Analyzes and optimizes SQL queries across different data warehouse platforms (Snowflake, BigQuery, Redshift, Databricks) with platform-specific recommendations.
原文の言語: 英語
Designs optimal windowing strategies for stream processing
原文の言語: 英語
Alibi explainability skill for counterfactual explanations, anchors, and trust scores.
原文の言語: 英語
Arize AI skill for production ML monitoring, embedding drift, and performance analysis.
原文の言語: 英語
BentoML skill for model packaging, serving, and containerization.
原文の言語: 英語
Dataset versioning skill using DVC for tracking data changes, managing data pipelines, and ensuring reproducibility.
原文の言語: 英語
Evidently AI skill for data drift detection, model performance monitoring, target drift analysis, and automated reporting for ML systems in production.
原文の言語: 英語
Fairness assessment skill using Fairlearn for bias detection, mitigation, and compliance reporting.
原文の言語: 英語
Feature store management skill for online/offline feature serving, feature registration, and training-serving consistency.
原文の言語: 英語
Data quality validation skill using Great Expectations for schema validation, expectation suites, data documentation, and automated data quality checks in ML pipelines.
原文の言語: 英語
Jupyter notebook execution skill for running notebooks programmatically and extracting outputs.
原文の言語: 英語
Kubeflow Pipelines skill for ML workflow orchestration, component management, and Kubernetes-native ML.
原文の言語: 英語
LIME-based local explanation skill for individual predictions across tabular, text, and image data.
原文の言語: 英語
MLflow integration skill for experiment tracking, model registry, and artifact management. Enables LLMs to log experiments, compare runs, manage model lifecycle, and retrieve artifacts through the MLflow API.
原文の言語: 英語
Model documentation skill for generating model cards following Google's model card framework.
原文の言語: 英語
Optuna integration skill for automated hyperparameter optimization with advanced search strategies, pruning, multi-objective optimization, and visualization capabilities.
原文の言語: 英語
Automated DataFrame analysis skill for statistical summaries, missing value detection, data type inference, and memory optimization recommendations.
原文の言語: 英語
PyTorch model training skill with custom training loops, gradient management, and GPU optimization.
原文の言語: 英語
Distributed computing skill using Ray for parallel training, hyperparameter search, and resource management.
原文の言語: 英語
Seldon Core deployment skill for model serving, A/B testing, and canary deployments on Kubernetes.
原文の言語: 英語
SHAP-based model explainability skill for feature attribution, summary plots, and interaction analysis.
原文の言語: 英語
Scikit-learn model training skill with cross-validation, hyperparameter tuning, pipeline construction, and model serialization. Enables automated ML model development using scikit-learn's comprehensive toolkit.
原文の言語: 英語
TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration.
原文の言語: 英語
Weights & Biases integration skill for experiment tracking, hyperparameter sweeps, and artifact versioning.
原文の言語: 英語
WhyLabs integration skill for ML observability, profile logging, and anomaly detection.
原文の言語: 英語
Run accessibility audits with axe-core and screen reader testing for desktop applications
原文の言語: 英語