data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Provides structured guidance and best practices for Large Language Model (LLM) fine-tuning, model selection, and troubleshooting.
Master the foundational syntax and precision parameterization required for BUGS and JAGS statistical modeling.
Provides foundational knowledge for writing, reviewing, and optimizing high-performance Stan 2.37 Bayesian models.
Implements advanced Bayesian time series analysis using Stan and JAGS for probabilistic forecasting and state-space modeling.
Implements and optimizes hierarchical Bayesian models with support for partial pooling and advanced parameterization techniques.
Evaluates Bayesian model convergence and sampling performance using MCMC diagnostics for Stan and JAGS frameworks.
Analyzes CSV files automatically to provide statistical summaries, domain-specific insights, and relevant visualizations without requiring user intervention.
Builds, optimizes, and executes quantum circuits and algorithms on real hardware and high-performance simulators.
Converts chemical structures into numerical representations for molecular machine learning and drug discovery workflows.
Optimizes AI agent behavior through specialized prompt engineering patterns and best practices for complex, autonomous workflows.
Implements comprehensive evaluation frameworks to measure LLM application quality using automated metrics, human feedback, and comparative benchmarks.
Builds high-performance Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search to ground LLMs in external data.
Implements advanced prompt engineering techniques to maximize LLM performance, reliability, and reasoning capabilities in production environments.
Train, deploy, and manage distributed neural networks within E2B sandboxes using the Flow Nexus ecosystem.
Implements high-performance adaptive learning and memory distillation for AI agents using the ultra-fast AgentDB vector engine.
Orchestrates multi-agent AI systems for parallel task execution and intelligent workflow coordination using dynamic topologies.
Implements high-performance, Rust-powered tokenization for training and deploying custom NLP models with speed and precision.
Provides expert guidance for building, configuring, and optimizing Retrieval-Augmented Generation (RAG) pipelines.
Generates optimized LlamaFarm configuration files from natural language descriptions for RAG and document processing workflows.
Generates vector embeddings for project-local skills and agents to enable intelligent semantic search and smart routing within Claude Code.
Enhances Claude Code with Gemini's multimodal analysis, million-token context, and real-time web search capabilities.
Automates the creation, editing, and analysis of professional Excel spreadsheets with advanced formula support and industry-standard financial modeling.
Provides expert-level GIS analysis, property lookups, and policy research for Solano County, California.
Indexes and manages multi-format reference documents to enhance RAG-based context retrieval during development tasks.
Standardizes the development of Python machine learning experiments using specific layout, execution, and asset management patterns.
Validates speleothem-based paleoseismic research by testing cave geochemical records against modern earthquake catalogs.
Builds and orchestrates sophisticated AI agents and multi-agent workflows using the Microsoft Agent Framework for .NET applications.
Generates high-quality videos and animations from text or images using the Google GenAI Veo 3.1 model.
Builds advanced financial models including DCF analysis, Monte Carlo simulations, and scenario planning for data-driven investment decisions.
Integrates 300+ AI models into Claude Code for specialized tasks, high-fidelity image generation, and cross-model reasoning.
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