data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Optimizes mean-reversion trading strategy parameters through real-time performance analysis and pattern identification.
Performs hydrological modeling and streamflow forecasting using Julia-based classical and machine learning models.
Analyzes text data to identify emotional tone and classify sentiment as positive, negative, or neutral.
Optimizes LLM prompts to minimize token usage, reduce operational costs, and enhance model response quality through automated refinement.
Optimizes AI agent performance through Anthropic-based context engineering and prompt structure standards.
Converts text and long-form markdown documents into high-quality audio locally using the Kokoro-82M model optimized for Apple Silicon.
Refines and compresses LLM prompts to minimize token usage, lower operational costs, and maximize response quality.
Master core machine learning pillars including data preprocessing, feature engineering, and robust model evaluation pipelines.
Provides specialized functions for hydrological modeling and climate data processing within the Julia environment.
Streamlines the development, validation, and systematic documentation of trading strategies and market edges.
Guides users through a scientifically rigorous five-phase hypothesis testing process to eliminate bias and p-hacking in data analysis.
Validates the ethical implications and fairness of AI/ML models and datasets to ensure responsible development and bias mitigation.
Orchestrates multiple AI model providers to optimize development workflows for cost, latency, and reasoning capability.
Performs automated exploratory data analysis and generates comprehensive markdown reports for over 200 scientific file formats.
Automates the creation, configuration, and deployment of machine learning demos on Hugging Face Spaces using Gradio, Streamlit, and ZeroGPU.
Equips Claude with specialized knowledge for statistical analysis, regression modeling, and reproducible data science script organization.
Engineers and optimizes high-quality LLM prompts across multiple models using established best practices and systematic refinement techniques.
Generates rigorous experimental frameworks to validate research hypotheses with statistical significance and comprehensive baseline comparisons.
Automates professional-grade spreadsheet creation, editing, and analysis with a focus on formula integrity and financial modeling standards.
Transforms and analyzes large datasets using DuckDB SQL directly within the Claude Code environment.
Accesses, downloads, and analyzes French public open data from data.gouv.fr using a specialized Python library and integrated documentation.
Provides programmatic access and analysis of comprehensive pharmaceutical data from the DrugBank database for drug discovery and pharmacology research.
Simplifies complex data analysis in Excel using advanced formulas, Pivot Tables, and Power Query automation.
Applies idiomatic JAX patterns and best practices to optimize scientific computing and machine learning workflows in Python.
Generates publication-quality scientific visualizations using TMLR styling and LaTeX rendering for research and academic reports.
Optimizes LLM performance and reliability through advanced prompt engineering techniques and structured reasoning patterns.
Optimizes LLM performance through advanced prompt engineering patterns, RAG system design, and agentic architecture implementation.
Creates and manages professional spreadsheets with dynamic formulas, financial formatting standards, and advanced data analysis capabilities.
Optimizes large-scale data staging on HPC environments using rsync, bash, and SLURM to ensure data integrity and script reliability.
Builds sophisticated AI-powered applications and blockchain solutions using modern LLMs, machine learning frameworks, and Web3 technologies.
Scroll for more results...