data science & ml向けのClaudeスキルを発見してください。53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。
Automates the end-to-end processing and curation of bulk RNA-seq datasets for VEuPathDB genomic resources.
Generates standardized Jupyter notebooks for fantasy football data analysis, integrating DuckDB connections, dbt mart queries, and professional visualization patterns.
Executes structured, atomic tasks for fantasy football analytics, FASA optimization, and trade intelligence within a standardized sprint framework.
Manages end-to-end bioinformatics research by orchestrating hypothesis-driven experiment planning, execution, and standardized lab notebook documentation.
Trains and fine-tunes language models using Transformer Reinforcement Learning methods on fully managed Hugging Face cloud GPU infrastructure.
Streamlines single-cell omics analysis through deep learning-based data integration, reference mapping, and model surgery techniques.
Analyzes single-cell omics data using deep probabilistic models for integration, batch correction, and differential expression.
Facilitates single-cell RNA-seq analysis of cell-cell communication and ligand-receptor interactions using the CellPhoneDB framework.
Facilitates the development and orchestration of collaborative multi-agent AI systems and automated workflows.
Facilitates the setup, optimization, and management of molecular mining operations on Bittensor Subnet 68 for decentralized drug discovery.
Automates complex data science workflows using a multi-agent architecture and optimized model routing for efficient, iterative data analysis.
Crafts production-ready LLM prompts, agent definitions, and system instructions optimized for Claude and GPT models.
Explores datasets and generates interactive visualizations in marimo notebooks using Polars and Plotly Graph Objects.
Search and synthesize local vector RAG stores using an AI-powered graphical interface.
Accesses and analyzes ES/NQ futures market data using Databento's high-fidelity platform with a cost-optimized workflow.
Identifies and resolves memory exhaustion issues in Python and PyTorch applications, specifically targeting matplotlib figures and tensor accumulation.
Enforces adherence to PRISM architectural patterns by validating the implementation of Runner and Trainer classes during refactoring.
Assists medical professionals by extracting symptoms from natural language, identifying potential diagnoses, and suggesting clinical next steps.
Implements and trains reinforcement learning algorithms to create autonomous agents that improve through experience.
Detects narrative manipulation and propaganda patterns in text and URLs using the Narrative Credibility Index (NCI) Protocol.
Produces comprehensive, well-sourced research reports using an iterative diffusion-based refinement methodology.
Enhances Claude's problem-solving capabilities using advanced search strategies like Beam Search and Monte Carlo Tree Search.
Implements high-performance adaptive learning and experience replay for AI agents using the AgentDB vector engine.
Empowers AI agents with adaptive learning and pattern recognition to optimize workflows and decision-making strategies through experience.
Automates the creation of robust data ingestion providers using standardized patterns for registry mapping, storage abstraction, and metadata tracking.
Optimizes LangGraph application performance by iteratively refining prompts and node-level processing logic based on quantitative evaluation criteria.
Interacts with diverse large language models through a command-line interface to perform tasks like prompt execution, data extraction, and embedding management.
Converts audio files into high-quality timestamped transcriptions using NVIDIA's Parakeet model optimized for Apple Silicon.
Manages and routes requests across multiple AI providers including Anthropic, Ollama, and HuggingFace.
Streamlines the development of AI-powered features within the Moodle LMS using the official AI Subsystem for version 4.5 and above.
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