data science & ml向けのClaudeスキルを発見してください。61個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Systematically evaluates research study quality and risk of bias using context-adaptive methodologies and industry-standard appraisal tools.
Integrates qualitative and quantitative research data to generate rigorous meta-inferences and professional joint displays.
Preprocesses and normalizes audio files using FFmpeg to optimize them for high-accuracy speech-to-text transcription.
Eliminates HOLD bias in reinforcement learning trading models by calibrating reward functions and slippage penalties.
Automates the recording of actual trading results against predicted signals to enable accurate performance metrics and model retraining.
Enforces reproducible research and academic writing standards for Quarto and RMarkdown documents to eliminate generic AI-generated content.
Implements and trains autonomous agents using nine specialized reinforcement learning algorithms for self-improving behavior.
Train, deploy, and manage distributed neural networks across sandboxed E2B environments using multiple architectures and federated learning.
Analyzes US fiscal deficit expansion and Treasury risk scenarios during periods of rising unemployment and high GDP growth.
Trains Reinforcement Learning models across multiple market timeframes with automated data resampling and professional market alignment.
Corrects financial logic in trading simulators to prevent inflated equity curves and inaccurate drawdown metrics.
Validates machine learning training scripts and configurations to ensure path accuracy, weight consistency, and environment compatibility.
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.
Manages version compatibility between trained trading models and live trading environments by embedding metadata into checkpoints.
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.
Standardizes import patterns and file paths for MaxFuse Jupyter notebooks to ensure reliable package integration.
Optimizes financial market universe selection using a multi-stage pipeline and SQLite-backed data management.
Calibrates reinforcement learning reward scales to eliminate unrealistic drawdown metrics in algorithmic trading models.
Extracts structured data from complex PDFs, scanned documents, and multi-column layouts using the advanced Docling engine and Granite vision-language models.
Transforms complex business data into actionable insights and strategic recommendations using advanced analytics and predictive modeling.
Automates quality control for stitched microscopy images by detecting saturation failures and visible tile grid patterns.
Transforms raw data into persuasive narratives and executive-ready presentations using proven storytelling frameworks and visualization techniques.
Guides the design, evaluation, and implementation of robust LLM-powered projects and agentic architectures.
Analyzes and describes visual content from images and PDF files using the Gemini 1.5 Flash vision model.
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.
Extracts and converts PDF documents into LLM-friendly formats like Markdown to support RAG pipelines and document analysis.
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