data-science

Activate the data-science team to collaboratively work on data science and ML tasks

Show data-science team status and recent activity

Performs statistical analysis, creates visualizations, and interprets results

Builds data pipelines, ETL processes, and data infrastructure

Analyzes datasets, identifies patterns, and understands data structure

Develops machine learning models, feature engineering, and model optimization

Manages model deployment, monitoring, and CI/CD for ML systems

Data pipeline patterns, ETL/ELT best practices, data storage options, and data quality techniques

Model selection guidelines, feature engineering techniques, hyperparameter tuning strategies, evaluation metrics, and common ML frameworks

Model deployment strategies, monitoring and drift detection, CI/CD for ML models, feature store concepts, and model versioning

Statistical methods and tests, hypothesis testing, A/B testing frameworks, time series analysis, and experimental design

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