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。
Architects high-performance AI prompts using advanced complexity-based standards, attention management, and structural optimization patterns.
Implements advanced agentic patterns to prevent context saturation and optimize parallel execution within Claude Code environments.
Creates, modifies, and analyzes professional Excel spreadsheets with automated formula recalculation and industry-standard financial formatting.
Optimizes AI models for resource-constrained edge devices using advanced quantization, memory management, and battery-smart inference patterns.
Performs rigorous statistical analysis, hypothesis testing, and APA-compliant reporting for academic and experimental research.
Queries and analyzes the OpenAlex database to search scholarly literature, track citations, and perform bibliometric analysis.
Provides a unified interface for rapid bioinformatics queries across 20+ genomic databases including Ensembl, AlphaFold, and NCBI.
Trains and deploys complex neural network architectures within distributed E2B sandbox environments using Flow Nexus.
Designs and implements autonomous AI agents with sophisticated tool use, memory systems, and multi-agent orchestration.
Architects and implements robust autonomous AI agents with sophisticated tool use, memory systems, and multi-agent orchestration.
Designs adaptive user-facing agent experts to create personalized product experiences and dynamic UX.
Automates end-to-end scientific research workflows from initial data analysis and hypothesis generation to publication-ready LaTeX manuscripts.
Automates professional Excel spreadsheet creation, financial modeling, and data analysis with error-free formula verification.
Conducts comprehensive market analysis, industry trend tracking, and market sizing calculations to drive data-informed business decisions.
Enables programmatic PDF manipulation, data extraction, and document creation using professional Python and command-line tools.
Processes whole slide images (WSI) for digital pathology by automating tissue detection and tile extraction for machine learning pipelines.
Manages large-scale scientific dataset transfers between remote Globus endpoints and high-performance computing clusters.
Performs high-performance genomic interval analysis, overlap detection, and machine learning tokenization using Rust-powered tools.
Corrects multi-action trading logic bugs and optimizes backtesting notebooks for Google Colab environments.
Builds high-performance, incremental AI data transformation pipelines for vector databases and knowledge graphs.
Integrates the Google Gemini CLI into Claude to provide large-context analysis, safe sandbox execution, and structured code modifications.
Streamlines astronomical data analysis and astrophysical research using the core Astropy Python ecosystem.
Optimizes KINTSUGI batch processing by enforcing GPU-only SLURM scheduling to achieve up to 25x speedups over CPU fallback.
Analyzes whole-slide pathology images and multiparametric data using specialized computational workflows and machine learning.
Implements granular skip-existing checks in Snakemake wrapper scripts to resume interrupted HPC jobs without re-processing completed channels.
Enhances multiplex immunofluorescence images by applying range-specific weights to remove background noise while preserving delicate biological signals.
Generates testable, evidence-based scientific hypotheses and experimental designs across multiple research domains.
Evaluates scientific research rigor by assessing methodology, statistical validity, and bias through established frameworks like GRADE and Cochrane ROB.
Accesses and analyzes global public statistical data through the Data Commons knowledge graph and Python API.
Generates comprehensive, 50+ page professional market research reports with consulting-grade analysis and high-fidelity visualizations.
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