发现data science & ml类别的 Claude 技能。浏览 61 个技能,找到适合您 AI 工作流程的完美功能。
Optimizes Apache Spark jobs through advanced partitioning, memory management, and shuffle tuning to improve performance and scalability.
Builds and deploys production-ready Agent Development Kit (ADK) agents with robust testing and multi-agent orchestration.
Extracts, structures, and converts complex Excel data into developer-friendly JSON and CSV formats.
Exports analysis results and query data into professional formats including CSV, JSON, Excel, and Markdown tables.
Analyzes, cleans, and visualizes Excel spreadsheet data using Python libraries like pandas and openpyxl.
Optimizes Claude's ability to process massive files and complex codebases using a recursive Probe-Extract-Confirm reasoning pattern.
Generates real-world evidence from observational data using advanced R-based causal inference and target trial emulation techniques.
Powers Claude with advanced visual perception to analyze images, process PDFs, and extract structured data from visual inputs.
Extracts tables, identifies sections, and summarizes content from complex PDF documents and technical reports.
Preprocesses and normalizes audio files using FFmpeg to optimize them for high-accuracy speech-to-text transcription.
Design, simulate, and analyze complex adaptive clinical trials using industry-standard R packages and Bayesian methods.
Evaluates scientific manuscripts and grant proposals for methodological rigor, statistical accuracy, and reporting standards.
Automates professional spreadsheet creation, data analysis, and financial modeling with industry-standard formatting and formula verification.
Builds production-grade AI systems using modern patterns like RAG, programmatic prompting, and Model Context Protocol (MCP).
Streamlines the end-to-end machine learning competition lifecycle including data handling, model training, and submissions.
Implements adaptive learning and meta-cognitive capabilities to help AI agents optimize strategies through experience and pattern recognition.
Performs comprehensive network meta-analyses in R using frequentist and Bayesian frameworks to compare multiple treatments simultaneously.
Instantiates sophisticated multi-agent architectures to handle complex reasoning, research, and implementation tasks.
Implements high-performance semantic vector search and intelligent document retrieval for RAG-based Claude Code workflows.
Implements comprehensive evaluation strategies for Large Language Model applications using automated metrics, human feedback, and rigorous benchmarking.
Converts research paper PDFs into structured, reproducible Markdown summaries for technical analysis and knowledge management.
Implements high-performance adaptive learning and memory distillation for autonomous agents using the AgentDB vector engine.
Manages persistent AI agent memory and reasoning patterns using high-performance vector storage and learning algorithms.
Builds and analyzes robust Bayesian statistical models using Stan-based R packages like brms and rstanarm.
Refines and expands acceptable ground-truth tools for Galaxy tool recommendation benchmarks through manual validation and IO compatibility analysis.
Builds and orchestrates end-to-end MLOps pipelines from data preparation and training through to production deployment.
Extracts and converts PDF documents into LLM-friendly formats like Markdown to support RAG pipelines and document analysis.
Builds sophisticated conversational interfaces and LLM-powered applications with advanced natural language understanding and context management.
Automates the generation of analytical features from horse racing data stored in PostgreSQL databases.
Synthesizes patient-level data across multiple studies using advanced meta-analysis methods and R statistical frameworks.
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