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。
Accelerates high-performance data analysis and manipulation using the lightning-fast Polars DataFrame library.
Processes and analyzes massive tabular datasets exceeding available RAM using lazy, out-of-core DataFrame operations.
Performs exact symbolic mathematics in Python, including algebraic solving, calculus, and matrix manipulations.
Models complex systems using process-based discrete-event simulation to optimize resources, queues, and time-based workflows.
Automates electronic lab notebook workflows by providing programmatic access to LabArchives for research data management and documentation.
Queries the NCBI ClinVar database to retrieve, interpret, and process human genetic variant clinical significance data.
Provides comprehensive access to the Human Metabolome Database for metabolite identification, chemical analysis, and biomarker discovery.
Conducts systematic, rigorous reviews of scientific manuscripts and grant proposals by evaluating methodology, statistics, and reporting standards.
Evaluates scientific manuscripts and grant proposals using a systematic toolkit for methodology, statistics, and reporting standards.
Performs comprehensive exploratory data analysis and generates detailed reports for over 200 scientific file formats.
Accesses global statistical data from Data Commons for demographic, economic, and environmental analysis.
Performs advanced statistical hypothesis testing, regression analysis, and Bayesian modeling with automated assumption checking and APA-style reporting.
Streamlines the development, deployment, and management of bioinformatics pipelines and data on the DNAnexus cloud genomics platform.
Explores and maps complex codebases using AST analysis to reduce token usage by 95% while maintaining structural visibility.
Accesses NIH Metabolomics Workbench to query over 4,200 studies, metabolite structures, and standardized biochemical nomenclature.
Generates testable, evidence-based scientific hypotheses and structured experimental designs to accelerate autonomous discovery.
Accesses and orchestrates over 600 scientific tools and databases for bioinformatics, drug discovery, and life sciences research workflows.
Aggregates and synthesizes perspectives from multiple AI agents to provide comprehensive, consensus-driven answers to complex queries.
Aggregates and synthesizes diverse perspectives from multiple AI agents to provide a consensus-driven answer to complex queries.
Optimizes LLM performance and designs production-grade agentic systems using advanced prompt engineering patterns and evaluation frameworks.
Provides expert guidance on statistical modeling, causal inference, and production-grade machine learning systems to drive data-driven decision-making.
Productionizes machine learning models and builds scalable MLOps systems using industry-leading frameworks and best practices.
Implements production-grade computer vision systems including object detection, segmentation, and real-time video processing using industry-standard frameworks like PyTorch and OpenCV.
Analyzes the McKinsey Ark repository to help developers understand, implement, and extend provider-agnostic agentic resource patterns.
Automates the generation of standardized Agent-as-a-Tool and function-based tools for the Strands SDK agent system.
Optimizes and structures system prompts for AI agents using Anthropic's context engineering principles and mandatory Python template escaping rules.
Integrates MiniMax's powerful text-to-speech engine to generate, clone, and design realistic voices directly within your development environment.
Automates the creation, editing, and analysis of complex spreadsheets including formulas, formatting, and professional layouts.
Automates the creation and management of clean, reproducible Jupyter notebooks for data experiments and educational tutorials.
Searches and retrieves academic literature across multiple scientific databases including arXiv, PubMed, and IEEE Xplore.
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