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。
Manage R package function and argument lifecycles using Tidyverse principles and the lifecycle package.
Provides comprehensive guidance on visual encoding, chart selection, and technical implementation for building accessible, high-performance data representations.
Performs comprehensive data cleaning, statistical analysis, and professional visualization using Python and pandas.
Integrates MiniMax's advanced image analysis capabilities into the OpenClaw platform for detailed visual interpretation and recognition.
Automatically identifies and activates specialized machine learning and AI development skills within Claude Code.
Automates the discovery and activation of specialized Information Retrieval and search engine optimization skills for advanced data tasks.
Optimizes AI interactions by applying Anthropic's official prompt engineering best practices to improve accuracy, consistency, and structure.
Optimizes and structures prompts for Claude using Anthropic’s official best practices and advanced design patterns.
Analyzes China A-share stocks using value investing principles and comprehensive financial data screening.
Streamlines the machine learning lifecycle by automating algorithm selection, advanced feature engineering, and rigorous statistical experimentation.
Designs sophisticated multi-agent system architectures, orchestration patterns, and robust tool schemas for autonomous AI workflows.
Automates machine learning lifecycles by implementing robust pipelines, production-grade model serving, and continuous monitoring.
Performs professional financial modeling, DCF valuation, and budget variance analysis to drive data-led strategic decision-making.
Designs, implements, and optimizes production-grade Retrieval-Augmented Generation (RAG) pipelines for high-performance AI applications.
Search, download, and read academic papers from arXiv directly within Claude using a hybrid API and web scraping approach.
Performs deep research and automated financial signal tracking to identify market trends and structured insights.
Optimizes workforce management through data-driven insights, predictive attrition modeling, and automated HR metric analysis.
Optimizes data manipulation and analysis workflows using high-performance, vectorized pandas patterns.
Orchestrates production-grade machine learning workflows, including feature engineering, automated training, and MLOps lifecycle management.
Optimizes large language models through parameter-efficient fine-tuning, automated dataset preparation, and production-grade performance benchmarking.
Optimizes and builds high-performance distributed data processing pipelines using Apache Spark and PySpark.
Designs, optimizes, and evaluates high-performance LLM prompts using advanced techniques like chain-of-thought and few-shot learning.
Builds validated, institutional-grade financial models including DCF, LBO, and M&A valuations with comprehensive scenario analysis.
Conducts rigorous, audit-ready financial analysis including ratio, trend, and variance assessments through a structured 5-phase workflow.
Streamlines the installation, provider configuration, and initialization of the Agent Brain RAG system for local or cloud-based document search.
Crafts high-quality AI instructions using the Genius Intern framework to maximize LLM performance and clarity.
Optimizes LLM prompts using the GEPA algorithm and DSPy framework with integrated observability and Pareto-based performance tuning.
Implements optimal document chunking strategies to enhance RAG system retrieval accuracy and maintain semantic context.
Builds type-safe, declarative AI services using LangChain4j patterns and Java interfaces with minimal boilerplate code.
Deploys and manages AI agents using the AWS Bedrock AgentCore suite of services for scaling, memory, and tool integration.
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