data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Implements comprehensive machine learning pipelines in R using the tidymodels ecosystem, from data preprocessing to model deployment.
Transforms raw data into validated Vega-Lite charts with intelligent type recommendation and automated configuration.
Implements industry-standard clinical trial design and statistical analysis workflows using regulatory-compliant R packages.
Standardizes Indirect Treatment Comparison (ITC) analyses in R using tidy modeling principles and reproducible workflow patterns.
Translates natural language into precise DBT semantic layer queries with automated filtering, visualization, and context-aware data exploration.
Implements and simulates complex adaptive clinical trial designs using industry-standard R packages like adaptr, rpact, and RBesT.
Implements comprehensive survival analysis workflows in R using tidy and traditional biostatistical frameworks.
Performs SQL data analysis, identifies trends, and generates comprehensive business intelligence reports directly within your workspace.
Performs advanced health economic evaluations including cost-effectiveness analysis, Markov modeling, and sensitivity analysis using R.
Executes, monitors, and optimizes DBT data transformation pipelines with intelligent error handling and performance reporting.
Automates professional spreadsheet creation, complex financial modeling, and data analysis with full support for formulas, formatting, and error-free recalculation.
Facilitates complex individual participant data (IPD) meta-analyses using tidy R workflows and advanced statistical modeling.
Provides expert guidance and R implementation patterns for survival analysis methods and non-proportional hazards in clinical trials.
Performs comprehensive genomics and bioinformatics statistical analysis using Bioconductor and R tidy modeling workflows.
Accesses and analyzes real-time SEC filings and financial statements with token-efficient data retrieval.
Optimizes machine learning models using advanced hyperparameter tuning strategies within the R tidymodels ecosystem.
Implements advanced Bayesian survival and time-to-event models with support for censoring and frailty effects.
Performs causal inference using genetic variants as instrumental variables through comprehensive R-based Mendelian Randomization workflows.
Provides comprehensive methodological guidance for Multilevel Network Meta-Regression (ML-NMR) using the multinma package and NICE DSU standards.
Implements advanced Bayesian regression models including linear, logistic, and robust variations using Stan and JAGS.
Provides expert methodological guidance and R code implementation for conducting rigorous pairwise meta-analyses following Cochrane and PRISMA standards.
Analyzes databases using SQL queries to generate actionable insights, trend reports, and data visualizations.
Implements and optimizes complex clinical trial designs including multi-arm, adaptive, and stratified patterns for biostatistical research.
Performs comprehensive diagnostic test accuracy analysis in R, including ROC curves, optimal cutpoints, and meta-analysis.
Implements a multi-layered memory architecture based on Mem0 research to boost AI accuracy and persistence across sessions.
Provides comprehensive methodological guidance and R implementation patterns for conducting rigorous network meta-analyses.
Streamlines clinical trial design and simulation using the Mediana framework for Clinical Scenario Evaluation (CSE).
Builds and analyzes robust Bayesian statistical models using Stan-based R packages like brms and rstanarm.
Builds sophisticated financial models and backtests algorithmic trading strategies with integrated risk management metrics.
Performs advanced causal mediation analysis to decompose total effects into direct and indirect effects using industry-standard R packages.
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