data science & ml向けのClaudeスキルを発見してください。61個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Processes and generates multimedia content including audio, video, images, and documents using the Google Gemini API.
Generates and refines structured physics analysis specifications using standardized templates and domain-specific best practices.
Provides comprehensive spreadsheet creation, financial modeling, and data analysis with strict formula preservation and industry-standard formatting.
Integrates comprehensive financial market data for stocks, forex, crypto, and technical indicators into the Claude environment.
Integrates Twelve Data for real-time and historical financial market data across stocks, forex, crypto, and technical indicators.
Automates Benchling R&D platform operations including sequence management, inventory tracking, and lab notebook entries via Python SDK and REST API.
Predicts high-accuracy 3D protein-ligand binding poses using diffusion-based deep learning for structure-based drug discovery.
Optimizes AI-assisted qualitative research through model selection guidance, cost estimation, and document processing strategies.
Synthesizes established metrics into structured driver assessments and integrated analytical reports using the HEAD framework.
Constructs and validates hierarchical data structures for qualitative research, transforming grounded participant language into abstract theoretical dimensions.
Queries and analyzes millions of scholarly works, authors, and citations using the OpenAlex open database API.
Queries and analyzes over 240 million scholarly works to conduct literature searches, citation analysis, and bibliometric studies.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank for drug discovery and pharmacological research.
Generates comprehensive financial models including DCF analysis, Monte Carlo simulations, and sensitivity testing for investment decisions.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank for bioinformatics research and drug discovery.
Provides comprehensive guidance and technical specifications for selecting and optimizing xAI Grok models within developer workflows.
Orchestrates 48+ specialized AI agents for autonomous cryptocurrency trading and market analysis across multiple exchanges.
Access and search the bioRxiv preprint server for life sciences research and automated full-text PDF retrieval.
Manages high-performance data buffers for real-time feature engineering and time-series analysis using Polars.
Manages, analyzes, and visualizes multi-modal spatial omics data using the SpatialData Python ecosystem and OME-NGFF standards.
Queries the ClinicalTrials.gov API v2 to search, retrieve, and export global clinical study data for medical research and patient matching.
Provides comprehensive guidance on leveraging Claude Opus 4.5, including reasoning control via the effort parameter and performance optimization.
Customizes and optimizes Amazon Bedrock foundation models through fine-tuning, continued pre-training, reinforcement learning, and model distillation.
Implements a multi-layered persistent memory architecture that enables AI agents to learn from experience and retain knowledge across sessions.
Implements production-grade LLM-as-a-Judge techniques for evaluating AI outputs through rigorous scoring, pairwise comparisons, and bias mitigation.
Integrates Alpha Vantage APIs to fetch real-time and historical market data, technical indicators, and financial fundamentals.
Streamlines the development of Python workflows using Awkward Array for jagged, nested, and record-based data structures.
Orchestrates complex LLM applications using graph-based abstractions, agentic design patterns, and modular task decomposition.
Implement efficient vector-based similarity search, semantic retrieval, and RAG patterns across major vector databases.
Proposes structured, data-driven experiment plans by analyzing historical training reports, logs, and research goals.
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