data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Generates professional Bazi (Four Pillars of Destiny) charts with solar time correction and elemental analysis using Python.
Integrates Google Gemini Web for high-quality image generation and persistent text conversations within Claude Code.
Powers traditional Chinese divination logic to provide structured decision-making signals based on classical Da Liu Ren texts.
Optimizes LLM agent performance by managing token density, memory architectures, and context window efficiency.
Formalizes natural language mathematical questions into Lean 4 and verifies them using the Harmonic Aristotle prover API.
Implements structured competitive prediction frameworks using Brier scores and systematic debiasing to enhance organizational forecasting accuracy.
Integrates Google Gemini's multimodal capabilities to process, analyze, and generate audio, video, images, and documents within Claude Code.
Enables Claude to identify and mitigate logical errors caused by focusing on visible successes while ignoring hidden failures.
Enhances decision-making by identifying statistical reversion in performance data and preventing false causal interpretations.
Streamlines academic literature reviews by discovering, ranking, and processing research papers from top scientific venues.
Discovers, prioritizes, and manages academic research papers for systematic literature reviews and methodology research.
Streamlines academic literature review and research paper discovery with automated prioritization and screening workflows.
Simplifies the design and analysis of complex control systems using the C11-based ctrlsys library.
Synthesizes multi-source information into structured knowledge, generating comprehensive reports, summaries, and knowledge graphs with automated contradiction resolution.
Analyzes complex optimization problems using evolutionary landscape metaphors to identify local traps and global optima.
Generates and optimizes high-impact features from raw datasets to boost machine learning model performance.
Processes and prepares data files for AI agent testing and deployment workflows.
Simulates complex systems from the bottom-up by defining simple rules for individual agents to observe emergent collective patterns.
Converts audio and video files into text transcripts with word-level timestamps using WhisperX.
Analyzes Lebanese market gaps using Ridge Regression to recommend optimal locations for new business branches based on demographic and competitor data.
Runs the interactive LLM Arena in the terminal to compare AI model outputs with high-quality markdown rendering.
Combats decision-making bias by anchoring probability assessments on statistical baseline frequencies before incorporating specific case details.
Implements expert annotation pipeline designs, quality assurance protocols, and scalable labeling systems for machine learning workflows.
Implements professional MLflow patterns for experiment tracking, model registry management, and reproducible ML pipelines.
Transforms raw data into optimized features to improve machine learning model performance and predictive accuracy.
Generates valid BioLM Protocol YAML files for protein engineering and bioinformatics pipelines.
Transforms experimental results into publication-ready LaTeX academic papers following professional research standards and style guides.
Architects and debugs complex OctoMesh ETL pipelines using YAML-defined data flows and transformations.
Implements real-time machine learning architectures for processing unbounded data streams with sub-100ms prediction latency.
Manages complex relationships and structured data entities across multiple domains using GraphRAG memory.
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