data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Predicts future values and identifies temporal patterns by analyzing historical time series data within the Claude Code environment.
Automates the fine-tuning and adaptation of pre-trained machine learning models for specialized datasets and tasks.
Automates the fine-tuning and adaptation of pre-trained machine learning models for custom datasets and specialized tasks.
Streamlines machine learning workflows in Python using scikit-learn for classification, regression, clustering, and data preprocessing.
Implements sophisticated persistent memory architectures for LLMs to manage short-term, long-term, and entity-specific context.
Implements high-performance Retrieval-Augmented Generation systems using advanced chunking, hybrid search, and reranking strategies.
Empowers Claude with image generation, real-time X/Twitter data access, and multi-model routing via an autonomous micropayment wallet.
Architects and orchestrates collaborative multi-agent AI teams using the CrewAI framework for complex, role-based workflows.
Empowers Claude Code with real-time X/Twitter data, photorealistic image generation, and multi-model routing via an autonomous micropayment wallet.
Empowers Claude with image generation, real-time X/Twitter data, and access to external AI models via autonomous micropayments.
Designs and orchestrates collaborative multi-agent AI teams using the role-based CrewAI framework.
Creates sophisticated, interactive data visualizations and custom SVG charts using the D3.js library.
Builds and orchestrates collaborative multi-agent AI teams using role-based design and structured task delegation.
Implements advanced Retrieval-Augmented Generation architectures including semantic chunking, hybrid search, and contextual reranking to optimize LLM document retrieval.
Implements advanced Retrieval-Augmented Generation patterns to optimize document retrieval and LLM context window efficiency.
Implements sophisticated tiered memory systems to help LLMs maintain long-term context and entity relationships across multiple sessions.
Implements persistent, tiered memory systems to help AI agents maintain long-term context and entity relationships.
Facilitates secure retrieval and rigorous validation of LSEG and Refinitiv financial data using the Python Data Library.
Uncovers hidden patterns, non-obvious correlations, and behavioral signals within complex datasets using investigative analysis techniques.
Automates the addition of new fal.ai models to the Renku pricing catalog by fetching schemas and researching real-time pricing data.
Creates, edits, and analyzes complex Excel spreadsheets with professional financial modeling standards and automated formula verification.
Creates interactive, publication-quality data visualizations and custom SVG graphics using D3.js.
Implements production-ready architectures for LLM applications, including RAG pipelines, autonomous agents, and prompt engineering workflows.
Enforces scientific rigor and theoretical correctness in software engineering tasks, prioritizing high-performance implementation and formal verification.
Builds sophisticated, interactive data visualizations and custom charts using d3.js across any JavaScript environment.
Applies uncompromising scientific rigor and formal verification to bridge the gap between theoretical computer science and high-performance implementation.
Integrates production-grade AI capabilities using optimized LLM patterns, structured outputs, and cost-efficient architectures.
Architects and implements autonomous AI agent systems using advanced tool-use patterns, memory strategies, and multi-agent orchestration.
Provides production-ready architectural patterns and implementation guides for building advanced LLM applications, RAG pipelines, and AI agents.
Applies uncompromising scientific rigor and formal verification to deliver high-performance, mathematically correct software implementations.
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