data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Powers semantic search and contextual retrieval across local libraries of academic papers and markdown documents.
Drafts publication-ready Results sections for quantitative sociology research based on established academic patterns.
Automates systematic literature reviews for sociology and academic research using the OpenAlex API and structured screening workflows.
Automates the creation of structured markdown reading notes from academic PDFs and EPUBs for sociology and social science research.
Conducts rigorous, publication-ready statistical analysis in Stata for sociology and social science research.
Drafts publication-ready methods and findings sections for qualitative research using advanced evidence presentation strategies.
Conducts systematic computational text analysis for sociology research using R or Python with a focus on validation and reproducibility.
Conducts publication-ready quantitative sociological research using phased R workflows and rigorous econometric methods.
Optimizes LLM prompts for high-accuracy text classification through a systematic, evaluation-driven workflow.
Automates the generation of scheduler-aware phylogenomic workflows from genome assemblies using single-copy orthologs.
Extracts and validates structured data from scientific PDF collections for systematic reviews and meta-analyses.
Optimizes LLM performance through advanced prompt design, agentic system architecture, and rigorous evaluation frameworks.
Simplifies running, converting, and serving Large Language Models on Apple Silicon using the MLX framework.
Enables natural language querying and exploration of biological and microbiome data within the KBase/BERDL Data Lakehouse.
Retrieves relevant past episodes and patterns from episodic memory to inform AI decision-making and task execution.
Accesses and integrates data from over 40 bioinformatics web services and databases using a unified Python API.
Performs differential gene expression analysis on bulk RNA-seq data using the Python implementation of DESeq2.
Provides comprehensive Python tools for astronomical data analysis, including celestial coordinates, physical units, and FITS file manipulation.
Integrates Google Gemini's advanced coding models into Claude Code for high-context refactoring, deep analysis, and automated file editing.
Accesses the Human Metabolome Database to retrieve chemical properties, clinical biomarkers, and spectral data for metabolomics research.
Sets up and executes probabilistic inference of ancestral geographic ranges on phylogenetic trees using BioGeoBEARS in R.
Automates scientific hypothesis generation and testing by combining observational data with literature insights using large language models.
Provides comprehensive tools for molecular analysis, chemical property calculation, and 3D structure generation within scientific research workflows.
Processes, filters, and analyzes mass spectrometry data for metabolomics research and chemical identification.
Automates the fine-tuning and adaptation of pre-trained machine learning models for custom datasets and specialized tasks.
Performs advanced regression analysis and predictive modeling to identify variable relationships and forecast data trends using automated statistical tools.
Performs advanced regression analysis and predictive modeling to identify trends and relationships within datasets.
Accesses and analyzes global public statistical data from authoritative sources via the Data Commons knowledge graph.
Analyzes text data to identify emotional tone, classifying content as positive, negative, or neutral for actionable insights.
Analyzes textual data to perform sentiment analysis, keyword extraction, and topic modeling using advanced natural language processing.
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