发现data science & ml类别的 Claude 技能。浏览 61 个技能,找到适合您 AI 工作流程的完美功能。
Automates the end-to-end scientific research lifecycle from initial data hypothesis to publication-ready LaTeX manuscripts.
Queries and analyzes genomic data from the Ensembl REST API for gene lookups, sequence retrieval, and variant analysis.
Builds robust Retrieval-Augmented Generation (RAG) systems to ground LLM applications with external data and private knowledge bases.
Provides domain-specific knowledge and experimental constraints for mechanistic interpretability research on Splatoon data models.
Manages Retrieval-Augmented Generation (RAG) indices to enable semantic search capabilities over BigQuery datasets.
Executes complex biomedical research tasks including genomics analysis, drug discovery, and clinical data interpretation through autonomous AI agents.
Analyzes athletic training data to track progress, optimize performance cycles, and identify potential injury risks.
Empowers biomedical researchers with autonomous agents for complex genomics, drug discovery, and clinical data analysis.
Generates professional PDF reports with formatted text, tables, and embedded visualizations using Python's reportlab library.
Automates Life Sciences R&D workflows by integrating Benchling registry, inventory, and notebook operations via Python SDK and REST API.
Automates the end-to-end MLOps lifecycle from data preparation and model training to production deployment and monitoring.
Generates professional, locally-executed PDF reports featuring formatted text, data tables, and embedded visualizations using the reportlab library.
Develops and trains Graph Neural Networks (GNNs) for deep learning on irregular structures and relational data.
Builds and validates Bayesian statistical models using PyMC's probabilistic programming framework.
Generates professional, publication-quality data visualizations and charts using Python's foundational plotting library.
Performs differential gene expression analysis using Python's DESeq2 implementation for bulk RNA-seq data.
Transforms complex academic papers into detailed, evidence-based narrative explanations with rigorous citation standards for research workflows.
Builds end-to-end MLOps pipelines from data preparation and model training through to production deployment.
Executes comprehensive geopolitical intelligence and data-driven research using the GDELT database and specialized analysis agents.
Generates professional, data-driven presentations and technical whitepapers with robust citation management and reproducibility standards.
Generates professional terminal-based and image-based visualizations to communicate data patterns and analytics results clearly.
Implements a systematic data quality remediation process to detect duplicates, handle outliers, and standardize inconsistencies for reliable analysis.
Simplifies computational molecular biology tasks including sequence manipulation, phylogenetic analysis, and programmatic NCBI database access.
Optimizes LLM performance through advanced prompt engineering, RAG architecture design, and agentic system orchestration.
Interacts with diverse large language models through a command-line interface to perform tasks like prompt execution, data extraction, and embedding management.
Transforms raw CSV data into interactive Plotly visualizations, comprehensive statistical reports, and professional multi-plot dashboards.
Builds type-safe, composable LLM applications in Ruby using the programmatic DSPy framework.
Analyzes athletic training logs to track progress, identify performance plateaus, and optimize recovery schedules using sports science principles.
Builds, trains, and deploys distributed neural networks within secure E2B sandbox environments using Flow Nexus.
Generates professional PDF reports featuring formatted text, data tables, and embedded visualizations using the reportlab Python library.
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