data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Builds production-grade AI applications using advanced RAG patterns, prompt engineering, and LLM orchestration frameworks.
Standardizes AI agent tuning by providing a command interface for bootstrapping, running, and monitoring optimization loops in Codex.
Automates systematic literature reviews by searching academic databases, synthesizing findings, and generating publication-ready documents with verified citations.
Conducts real-time academic research and literature reviews using Perplexity’s advanced Sonar models with automated citation generation.
Builds production-grade AI features using robust LLM integration patterns, prompt versioning, and cost-optimized RAG architectures.
Automates Langdock assistant management, knowledge base operations, and usage data exports through a unified CLI wrapper.
Implements production-grade LLM integration patterns, scalable prompt engineering, and cost-optimized AI architectures.
Extracts and analyzes metadata from NetCDF and CDL files into structured CSV format for documentation and data analysis.
Implements high-performance Retrieval-Augmented Generation systems by optimizing embeddings, chunking strategies, and vector search pipelines.
Implements high-performance Retrieval-Augmented Generation systems using sophisticated chunking, hybrid search, and reranking strategies.
Retrieves global atmospheric, land, and ocean climate reanalysis data from the Copernicus Climate Data Store using the CDS API.
Architects high-performance Retrieval-Augmented Generation systems using advanced embedding, chunking, and retrieval optimization strategies.
Architects high-performance Retrieval-Augmented Generation systems using advanced chunking strategies and optimized vector search algorithms.
Architects comprehensive evaluation frameworks for AI agents by defining metrics, datasets, and grading strategies.
Architects high-performance LLM prompts using structured patterns, few-shot examples, and systematic evaluation to maximize model reliability.
Implements sophisticated Retrieval-Augmented Generation patterns including semantic chunking, hybrid search, and reranking to improve LLM accuracy.
Expands Claude's capabilities with native image generation, real-time social media data, and cross-model reasoning via an autonomous micropayment wallet.
Builds reliable AI agents using robust patterns like ReAct and Plan-Execute while prioritizing guardrails and self-correction.
Modifies Matplotlib plots through visual browser-based annotations and AI-powered code updates.
Architects high-performance LLM prompts using structured design patterns and systematic evaluation techniques.
Optimizes Large Language Model performance through advanced prompting patterns, systematic testing, and structured template systems.
Optimizes token usage and reduces operational costs when delegating tasks to the Gemini CLI.
Generates publication-quality scientific diagrams and architectural schematics with automated AI quality review.
Integrates cutting-edge AI and machine learning capabilities into applications using LLM APIs, vector databases, and RAG architectures.
Architects high-performance prompts and structured system instructions to optimize Large Language Model accuracy and reliability.
Designs resilient contingency module architectures to manage failure scenarios within AI governance frameworks.
Enforces absolute scientific rigor and theoretical correctness in software engineering and implementation tasks.
Extends Claude’s capabilities with real-time X/Twitter data, AI image generation, and multi-model routing via an integrated micro-payment wallet.
Expands Claude's capabilities with image generation, real-time X/Twitter data, and access to external LLMs via autonomous micropayments.
Builds, evaluates, and deploys code-first AI agents and multi-agent systems using Google's Agent Development Kit.
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