data science & ml向けのClaudeスキルを発見してください。61個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Extracts and verifies information deltas between Claude.ai conversation exports using ACSets morphisms and bisimulation verification.
Accelerates scientific discovery by automatically generating, testing, and refining hypotheses from datasets and research literature using LLMs.
Generates professional, publication-ready clinical decision support documents and biomarker-stratified cohort analyses for pharmaceutical and clinical research.
Extracts narrative arcs, measures token novelty, and generates causality graphs from text and code repositories.
Accelerates reinforcement learning workflows through high-performance parallel environment simulation and optimized PPO training.
Queries the NHGRI-EBI GWAS Catalog to retrieve genetic variants, SNP-trait associations, and comprehensive genomic summary statistics.
Optimizes AI agent performance using Anthropic-aligned context engineering and prompt structuring principles.
Performs fast nonlinear dimensionality reduction and manifold learning for high-dimensional data visualization and clustering.
Provides a comprehensive Clojure library for symbolic mathematics, automatic differentiation, and classical mechanics simulation based on SICM concepts.
Manages AI research environments, evaluation pipelines, and hosted reinforcement learning runs through the Prime Intellect platform.
Facilitates advanced topological computation and chemputer configuration within the plurigrid ecosystem.
Validates and executes Aptos blockchain operations while managing data science notebooks in the World D ecosystem.
Optimizes complex problem-solving through topological logic and advanced resolution patterns.
Implements and manages neural networks that adapt, grow, or prune their topology during training to optimize capacity and prevent catastrophic forgetting.
Coordinates Kubeflow MLOps workflows and Aptos blockchain operations using a triadic synthesis system.
Facilitates exploratory abductive reasoning through interactive hypothesis-test loops for color spaces and topological models.
Implements formal model structures and homotopical algebra frameworks for BCI signal chains and topological computing.
Coordinates multi-agent systems and graph neural networks using sheaf Laplacians for distributed consensus and harmonic inference.
Implements colored operads and A-infinity structures to ensure mathematically consistent multi-input signal processing pipelines.
Implements sheaf neural network coordination and graph Laplacian operators for multi-agent consensus and harmonic inference.
Integrates fal.ai audio models for high-accuracy speech-to-text, premium text-to-speech, and advanced voice cloning.
Implements differential forms and exterior calculus on signal manifolds to bridge differential geometry and topological data analysis.
Models complex feedback systems and strategic dynamics using reinforcing and balancing loops with Lotka-Volterra semantics.
Replaces temporal sequencing with deterministic seed-chaining and color derivations for verifiable state transitions.
Generates mass-action ODEs and dynamic simulations for epidemiological and ecological systems using stock-and-flow diagrams.
Implements Möbius inversion on posets and lattices to solve complex combinatorial problems, graph coloring, and centrality analysis.
Enables interdisciplinary synthesis across mathematics, music, and philosophy using structural morphisms and ontological world-hopping.
Generates group-theoretic structures and computational algebraic objects for the Plurigrid ASI ecosystem.
Analyzes graph topology using the Ihara zeta function and non-backtracking spectral methods to identify prime cycles and community structures.
Analyzes mathematical theorem dependencies using spectral random walks to discover comprehension neighborhoods and proof patterns.
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