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。
Designs and implements robust multi-agent systems to overcome context limits and handle complex, parallelizable tasks.
Implements robust LLM-as-a-Judge evaluation techniques to measure, compare, and optimize the quality of AI-generated outputs.
Design and implement advanced memory architectures to help AI agents persist state, maintain entity consistency, and reason over structured knowledge.
Integrates Hyperspell’s long-term memory and RAG capabilities into your project with automated configuration and SDK setup.
Provides rigorous, PhD-level critiques of academic manuscripts and research methodologies to ensure high-impact scholarly standards.
Bootstraps a production-ready LangChain TypeScript project with optimal configuration for AI agents and LangGraph.
Maps LinkML enum permissible values to verified ontology terms and CURIEs using the Ontology Access Kit (OAK).
Optimizes AI prompts using research-backed frameworks and production-ready templates to ensure high-quality, cost-effective model outputs.
Implements robust pipes-and-filters architectures for complex ETL, media processing, and data transformation workloads.
Automates complex quantum chemistry workflows and molecular simulations through a high-level cloud-based Python API.
Conducts real-time academic and technical research using Perplexity Sonar models via OpenRouter to provide cited findings, statistical data, and deep analytical reasoning.
Connects Claude to the K-Dense Web AI co-scientist platform for executing complex, end-to-end scientific research workflows.
Facilitates the development and training of quantum machine learning models using automatic differentiation and hybrid quantum-classical workflows.
Implements high-performance persistent memory and context management for AI agents using AgentDB and vector storage.
Extends pandas with spatial operations for managing, analyzing, and visualizing vector geographic data types.
Generates, remixes, and manages high-quality AI videos using OpenAI’s Sora API via a specialized CLI.
Configures Ollama as a local embedding provider to enable private, offline semantic code search within GrepAI.
Simulates and analyzes open quantum systems, master equations, and decoherence using the Quantum Toolbox in Python.
Enables high-performance semantic vector search and intelligent document retrieval for RAG systems and knowledge bases.
Optimizes semantic code search by configuring precise file splitting and embedding parameters within GrepAI.
Implements nine reinforcement learning algorithms to train autonomous agents that improve through experience.
Generates publication-quality scientific diagrams and architectural schematics using AI-driven iterative refinement.
Performs advanced numerical computing, matrix operations, and scientific visualization using MATLAB and GNU Octave syntax.
Generates interactive, publication-quality Python charts and dashboards for data exploration and presentation.
Builds visually engaging, research-backed scientific presentations and slide decks for academic and professional talks.
Queries and downloads large-scale public cancer imaging datasets from the NCI Imaging Data Commons for AI training and medical research.
Optimizes agent behavior by automatically identifying the active LLM and adjusting execution configurations for maximum cross-model compatibility.
Builds, optimizes, and executes quantum circuits on IBM Quantum hardware and high-performance simulators using the world's most popular SDK.
Analyzes high-density Neuropixels recordings with automated preprocessing, spike sorting, and AI-assisted quality curation.
Builds, simulates, and executes quantum circuits on Google Quantum AI hardware and cloud providers.
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