data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Analyzes CSV files automatically to provide statistical summaries, domain-specific insights, and relevant visualizations without requiring user intervention.
Builds and optimizes reactive Python notebooks using marimo for interactive data analysis, dashboards, and machine learning workflows.
Facilitates creative research ideation and exploratory scientific problem-solving through structured conversational partnership.
Builds reactive Python notebooks, interactive dashboards, and data-driven applications using the marimo framework.
Manages large N-dimensional arrays with chunking and compression for high-performance scientific computing and cloud storage.
Builds, optimizes, and executes quantum circuits and algorithms on real hardware and high-performance simulators.
Implements multi-objective and single-objective optimization algorithms to solve complex engineering and mathematical problems.
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.
Manages fast, reproducible scientific Python environments by unifying the conda and PyPI ecosystems.
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.
Provides comprehensive financial frameworks for modeling, valuation, corporate finance decisions, and advanced statement analysis.
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.
Identifies statistical outliers and patterns in batch or streaming datasets using specialized machine learning backends.
Simplifies working with pre-trained transformer models for NLP, computer vision, and audio tasks within Claude Code.
Orchestrates the end-to-end creation of publication-quality AI/ML benchmark reports with high-resolution diagrams and PDF export.
Implements high-performance, Rust-powered tokenization for training and deploying custom NLP models with speed and precision.
Develops reactive Python notebooks and interactive dashboards using the marimo framework.
Creates publication-quality statistical graphics and complex data visualizations using a high-level Python interface.
Automates academic literature search and technical research using Perplexity's Sonar models with intelligent reasoning selection.
Provides expert guidance for building, configuring, and optimizing Retrieval-Augmented Generation (RAG) pipelines.
Conducts comprehensive, multi-database literature searches and synthesizes findings into professionally formatted research documents with verified citations.
Evaluates the rigor of scientific claims by assessing methodology, identifying biases, and grading evidence quality using standardized frameworks.
Enables real-time, AI-powered web searches with cited sources and advanced reasoning capabilities through the Perplexity model family.
Generates optimized LlamaFarm configuration files from natural language descriptions for RAG and document processing workflows.
Implements rigorous statistical modeling, econometrics, and time series analysis using Python's statsmodels library.
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