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。
Transforms RDF context into Belief-Desire-Intention (BDI) architectures to enable formal cognitive reasoning and rational agency in AI agents.
Simplifies the development, deployment, and management of cloud-based genomics pipelines on the DNAnexus platform.
Automates complex biomedical research tasks including genomics, drug discovery, and clinical analysis through autonomous multi-step reasoning.
Implements persistent, high-performance memory and learning patterns for AI agents using AgentDB vector storage.
Implements persistent, high-performance memory and learning patterns for stateful AI agents using AgentDB.
Builds and optimizes quantum circuits using automatic differentiation and seamless integration with PyTorch, JAX, and TensorFlow.
Performs rigorous statistical modeling, econometric analysis, and hypothesis testing using Python's statsmodels library.
Processes and manipulates medical imaging data in the DICOM standard using Python and NumPy.
Automates complex biomedical research tasks including genomics, drug discovery, and clinical analysis using autonomous AI reasoning and code execution.
Executes complex autonomous research tasks across genomics, drug discovery, and clinical analysis using integrated biomedical databases.
Solves complex single and multi-objective optimization problems using evolutionary algorithms and Pareto-optimal analysis.
Automates end-to-end scientific research workflows from data hypothesis generation to publication-ready LaTeX papers.
Executes complex autonomous biomedical research tasks across genomics, drug discovery, and clinical analysis using LLM-driven code execution and integrated biological databases.
Automates life sciences research workflows by integrating with the Benchling R&D platform for sample tracking, sequence management, and electronic lab notebooks.
Simplifies computational molecular biology tasks including sequence analysis, structural bioinformatics, and programmatic NCBI database access.
Accesses and processes the COSMIC database for somatic mutations, Cancer Gene Census, and precision oncology research.
Automates the end-to-end scientific research lifecycle from data analysis and hypothesis generation to publishing LaTeX-formatted papers.
Streamlines the design and construction of autonomous AI agents using a capability-driven framework and iterative architectural patterns.
Generates and edits high-quality images using Google's Gemini-3-pro-image-preview model via the google-genai Python library.
Builds robust AI-powered features using standardized patterns for prompt engineering, RAG workflows, and multi-provider LLM integrations.
Builds robust AI-powered applications through advanced prompt engineering, RAG implementation, and resilient API integration patterns.
Architect and implement production-grade Retrieval-Augmented Generation systems using LangChain and Qdrant vector stores.
Streamlines research paper collections by deduplicating entries and ranking them to create high-quality core datasets for academic analysis.
Audits research outlines by analyzing evidence coverage and mapping redundancy to ensure a structured, verifiable foundation.
Implements high-performance, accessible, and perceptually accurate data visualizations using industry-standard libraries and algorithms.
Generates high-performance text embeddings for RAG systems, semantic search, and document clustering using the Gemini API.
Integrates Google Gemini AI models using the latest high-performance SDK for text, multimodal, and agentic workflows.
Integrates Google Gemini's managed RAG system to build searchable document knowledge bases with automatic chunking, embeddings, and citations.
Enables high-performance AI model inference on Cloudflare’s global GPU network for text, image, and embedding generation.
Implements advanced AI backend logic using Vercel AI SDK versions 5 and 6, facilitating model orchestration, agentic workflows, and seamless version migrations.
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