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。
Performs high-performance computational fluid dynamics simulations and spectral analysis using Python.
Performs state-of-the-art diffusion-based molecular docking to predict 3D binding poses of small molecule ligands to protein targets.
Generates structured, data-driven scientific research reports by analyzing repository data and verifying metrics against technical standards.
Orchestrates end-to-end machine learning pipelines from automated data preparation through model training, validation, and production deployment.
Performs constraint-based metabolic modeling and systems biology simulations using the COBRApy Python library.
Streamlines molecular machine learning workflows for drug discovery, property prediction, and materials science using the DeepChem library.
Decomposes complex computational problems into three balanced, parallel components using GF(3) conservation and sheaf-theoretic gluing.
Facilitates automated protein design, sequence optimization, and wet-lab validation via a cloud-based laboratory platform.
Provides specialized guidance for molecular analysis, structural manipulation, and chemical property calculation using RDKit.
Optimizes LLM context windows to maximize reasoning quality while minimizing token costs and latency.
Simplifies the creation, orchestration, and deployment of production-grade AI agents using Google's Agent Development Kit.
Automates complex spreadsheet creation, financial modeling, and data analysis with formula integrity and industry-standard formatting.
Generates standardized Python scripts for analyzing model performance and creating publication-ready LaTeX tables and figures.
Standardizes machine learning model wrappers to provide a uniform interface for training, inference, and automated hyperparameter tuning.
Streamlines machine learning data preprocessing in R using standardized Tidymodels recipes patterns.
Manages a complete 4-stage pipeline from Python scripts to interactive notebooks and automated markdown documentation.
Manages end-to-end data pipelines across four stages from raw source ingestion to AI-ready datasets.
Facilitates the interactive drafting and refinement of LaTeX research papers through structured incubator documents and canonical data tracking.
Optimizes LLM performance and reliability through advanced prompting techniques like few-shot learning and chain-of-thought reasoning.
Integrates React and Vite applications with the Bodhi JS SDK to enable local LLM chat capabilities and seamless authentication.
Analyzes German U19 badminton ranking data from the DBV directly within Claude Code.
Orchestrates end-to-end MLOps pipelines from data preparation and model training to production deployment and monitoring.
Streamlines machine learning model endpoint deployment through unified packaging, inference function design, and multi-target deployment.
Develops production-grade AI applications using the OpenAI Agents SDK with multi-agent handoffs, voice integration, and robust error prevention.
Manages and orchestrates end-to-end neural network pipelines across algorithmic, tuning, and deployment layers.
Integrates Google's Gemini-3-pro-preview model into Claude Code for multimodal analysis, massive context processing, and real-time grounding.
Develops and manages reactive Python notebooks that function as pure-code files, interactive data apps, and reproducible scripts.
Facilitates complex decision-making through a multi-agent debate simulation that analyzes problems from diverse cognitive perspectives.
Manages complex spreadsheet tasks including professional financial modeling, data cleaning, and automated formula validation.
Designs and implements sophisticated LLM applications using the LangChain framework for complex AI workflows.
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