data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Balances algorithmic complexity with exploratory game theory to optimize proof discovery and extract World Extractable Value (WEV).
Analyzes and implements map projections using category theory and distortion metrics for precise geospatial transformations.
Provides a powerful Clojure environment for symbolic mathematics, automatic differentiation, and computational classical mechanics.
Optimizes LLM performance on Apple M-series chips using the MLX framework for high-efficiency local inference and fine-tuning.
Optimizes high-performance visualization for massive datasets exceeding 100 million points using Datashader and HoloViews.
Guides the selection, assumption checking, and interpretation of statistical hypothesis tests for rigorous research data analysis.
Implements rigorous random assignment procedures for scientific experiments to minimize selection bias and meet CONSORT standards.
Generates visual bifurcation diagrams to track stability transitions and behavior changes in dynamical systems.
Conducts quantitative synthesis by pooling effect sizes across multiple research studies to calculate summary effects and assess statistical heterogeneity.
Calculates and interprets standardized effect sizes to quantify the practical significance of research findings beyond statistical significance.
Provides a bidirectional bridge between S-expressions and Algebraic Julia data structures with high-performance navigation and transformation.
Minimizes experimental bias by implementing structured blinding protocols and objectivity standards for scientific research studies.
Systematically applies eligibility criteria during literature screenings to ensure rigorous and reproducible study selection in research workflows.
Evaluates methodological quality and potential biases in research studies using industry-standard frameworks for systematic reviews.
Optimizes and reasons about quantum circuits using graphical string diagrams and spider-based rewrite rules.
Enhances search precision by applying cross-encoder models to re-order and refine initial vector search results.
Interprets and reports statistical findings with accuracy, prioritizing effect sizes and confidence intervals over simple p-value significance.
Designs methodologically rigorous scientific experiments and research studies following NIH rigor standards and best practices.
Implements Cohesive Linear Homotopy Type Theory patterns to formalize interaction entropy and generate complex structural diagrams.
Analyzes and models complex dynamical systems using ergodicity principles where time averages equate to space averages.
Calculates statistical power and determines optimal sample sizes to ensure experimental designs meet rigorous scientific and funding standards.
Coordinates multi-agent systems and state transitions using GF(3) Galois Field conservation principles.
Linearizes complex nonlinear dynamics using Koopman operator theory to enable predictive modeling through observable space.
Linearizes nonlinear dynamical systems using Koopman operator theory to generate predictive models from observable data.
Performs vector similarity search and hierarchical clustering for agent skills using P-adic ultrametrics and MLX-powered embeddings.
Analyzes and traces the flow of ideas, topics, and behaviors across complex social and interperspectival networks.
Analyzes social network dynamics to trace idea adoption, influence flow, and interperspectival relationships.
Facilitates complex system modeling through a triadic balance of categorical structure, cybernetic agency, and phenomenological observation.
Implements a triadic framework balancing category theory, cybernetic agency, and phenomenological observation for complex system modeling.
Performs advanced geodesic calculations and Riemannian manifold operations for geospatial navigation and spherical geometry.
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