Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Identifies and prioritizes research gaps from systematic literature reviews to justify new studies and grant proposals.
Implements rigorous blinding protocols to minimize bias and ensure objectivity in experimental studies and clinical trials.
Analyzes histone modification ChIP-seq data to segment the genome into discrete chromatin states using ChromHMM workflows.
Implements standardized patterns for summing tax and benefit variables across entities using the adds attribute and add() function.
Filters raw BAM files by removing mitochondrial reads, PCR duplicates, and blacklisted regions to prepare genomic data for peak calling.
Automates the creation of robust data cleaning and preprocessing pipelines for Python-based data science workflows.
Generates visual phase portraits and vector fields for 2D dynamical systems to analyze state space behavior.
Automates safe, structure-preserving self-modification for AI agents using covariant transport and Darwin Gödel Machine evolution loops.
Implements time-symmetric, information-preserving computation patterns for Janus-style reversible logic and quantum-ready algorithms.
Implements high-performance adaptive learning and memory distillation for AI agents using the AgentDB vector engine.
Processes DICOM medical imaging files for metadata extraction, pixel data manipulation, and secure patient data anonymization.
Builds robust Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search to ground AI responses in proprietary data.
Configures and verifies scientific data acquisition systems by automating hardware discovery and parameter management.
Detects phase transitions and classifies dynamical system states using fixed-point distance measurements and self-loop closure verification.
Provides high-performance bidirectional data navigation and transformation for Julia collections, S-expressions, and ACSets.
Facilitates visual agent design and advanced reasoning configuration for building sophisticated, multi-step AI workflows.
Maps contributor interaction networks across GitHub to discover shared boundaries between research and developer communities.
Orchestrates end-to-end MLOps pipelines from data preparation and model training to production deployment and monitoring.
Axiomatizes the directed interval 0 → 1 to model irreversible processes and time-directed homotopy in synthetic infinity-categories.
Guides researchers through a systematic, phased workflow to produce publication-ready sociological research and quantitative R analysis.
Creates and optimizes elizaOS knowledge bases using RAG, smart chunking strategies, and semantic search integration.
Optimizes vector embedding selection and text chunking strategies for production-grade RAG and semantic search applications.
Identifies enriched transcription factor binding motifs in genomic regions or gene lists using the HOMER bioinformatics suite.
Navigates complex state spaces and possible worlds using Badiou-inspired ontology and triangle inequality constraints.
Implements a rigorous 6-phase framework for conducting and analyzing qualitative research with mandatory bias prevention and reproducible methodology.
Conducts systematic qualitative analysis of sociological interview data using grounded theory and theory-informed frameworks.
Optimizes LLM performance and reliability through advanced prompt engineering techniques like few-shot learning and chain-of-thought reasoning.
Evaluates research rigor, methodology, and statistical validity to perform critical analysis of scientific claims.
Architects sophisticated AI agent workflows using standardized LangGraph design patterns for complex state management.
Enables Claude to process, analyze, and generate audio, image, video, and document content using Google Gemini APIs.
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