Implements Change Data Capture patterns for real-time data integration
원문 언어: 영어
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이 저장소의 skills
SkillsMP는 a5c-ai/babysitter에서 2,079개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
a5c-ai/babysitter수집된 skill 2,079개 중 40개를 표시합니다.
Implements Change Data Capture patterns for real-time data integration
원문 언어: 영어
Analyzes and optimizes costs for cloud data platforms
원문 언어: 영어
Enriches data catalog entries with automated metadata
원문 언어: 영어
Extracts and maps data lineage from various sources including SQL, dbt, Airflow, and Spark, generating comprehensive lineage graphs for impact analysis.
원문 언어: 영어
Profiles data assets to assess quality dimensions, detect anomalies, and generate comprehensive data quality reports with actionable recommendations.
원문 언어: 영어
Analyzes dbt projects for best practices, performance, maintainability, and generates actionable recommendations for improvement.
원문 언어: 영어
Validates dimensional models against Kimball methodology best practices
원문 언어: 영어
Optimizes feature engineering pipelines and feature store configurations
원문 언어: 영어
Generates Great Expectations suites from data profiles and business rules
원문 언어: 영어
Selects and configures optimal incremental model strategies
원문 언어: 영어
Designs and optimizes Apache Kafka topics and configurations
원문 언어: 영어
Designs and optimizes One Big Table (OBT) patterns
원문 언어: 영어
Generates Slowly Changing Dimension implementations across platforms
원문 언어: 영어
Manages schema evolution and compatibility across data systems
원문 언어: 영어
Analyzes and optimizes SQL queries across different data warehouse platforms (Snowflake, BigQuery, Redshift, Databricks) with platform-specific recommendations.
원문 언어: 영어
Designs optimal windowing strategies for stream processing
원문 언어: 영어
Alibi explainability skill for counterfactual explanations, anchors, and trust scores.
원문 언어: 영어
Arize AI skill for production ML monitoring, embedding drift, and performance analysis.
원문 언어: 영어
BentoML skill for model packaging, serving, and containerization.
원문 언어: 영어
Dataset versioning skill using DVC for tracking data changes, managing data pipelines, and ensuring reproducibility.
원문 언어: 영어
Evidently AI skill for data drift detection, model performance monitoring, target drift analysis, and automated reporting for ML systems in production.
원문 언어: 영어
Fairness assessment skill using Fairlearn for bias detection, mitigation, and compliance reporting.
원문 언어: 영어
Feature store management skill for online/offline feature serving, feature registration, and training-serving consistency.
원문 언어: 영어
Data quality validation skill using Great Expectations for schema validation, expectation suites, data documentation, and automated data quality checks in ML pipelines.
원문 언어: 영어
Jupyter notebook execution skill for running notebooks programmatically and extracting outputs.
원문 언어: 영어
Kubeflow Pipelines skill for ML workflow orchestration, component management, and Kubernetes-native ML.
원문 언어: 영어
LIME-based local explanation skill for individual predictions across tabular, text, and image data.
원문 언어: 영어
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.
원문 언어: 영어
Model documentation skill for generating model cards following Google's model card framework.
원문 언어: 영어
Optuna integration skill for automated hyperparameter optimization with advanced search strategies, pruning, multi-objective optimization, and visualization capabilities.
원문 언어: 영어
Automated DataFrame analysis skill for statistical summaries, missing value detection, data type inference, and memory optimization recommendations.
원문 언어: 영어
PyTorch model training skill with custom training loops, gradient management, and GPU optimization.
원문 언어: 영어
Distributed computing skill using Ray for parallel training, hyperparameter search, and resource management.
원문 언어: 영어
Seldon Core deployment skill for model serving, A/B testing, and canary deployments on Kubernetes.
원문 언어: 영어
SHAP-based model explainability skill for feature attribution, summary plots, and interaction analysis.
원문 언어: 영어
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.
원문 언어: 영어
TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration.
원문 언어: 영어
Weights & Biases integration skill for experiment tracking, hyperparameter sweeps, and artifact versioning.
원문 언어: 영어
WhyLabs integration skill for ML observability, profile logging, and anomaly detection.
원문 언어: 영어
Run accessibility audits with axe-core and screen reader testing for desktop applications
원문 언어: 영어