data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Performs GSLIB-inspired geostatistical analysis including variogram modeling, kriging interpolation, and spatial simulations.
Automates the end-to-end formation evaluation pipeline from raw LAS/DLIS data to petrophysical analysis and 3D visualization.
Builds 2D numerical models for landscape evolution, erosion, hydrology, and geomorphology using the Landlab Python framework.
Performs complex geophysical forward modeling and inversion for subsurface physical property mapping.
Processes and models magnetotelluric (MT) geophysical data using the mtpy library to analyze subsurface resistivity.
Performs advanced formation evaluation and petrophysical analysis directly from well log data using industry-standard calculations.
Enforces epistemic quality in documentation to prevent LLM hallucinations in RAG systems.
Transforms pandas dataframes using AI-powered qualitative ranking, semantic deduplication, and research-based filtering.
Verifies and enforces epistemic quality in documents to prevent LLM hallucinations within RAG systems and knowledge bases.
Enforces epistemic quality and uncertainty markers in documents to prevent hallucinations in RAG systems and LLM workflows.
Computes surface wave dispersion curves and sensitivity kernels for layered Earth models with high-performance Numba acceleration.
Searches and downloads gravitational wave event data and strain files from the Gravitational Wave Open Science Center.
Searches, retrieves, and downloads scientific datasets, software, and research artifacts from the Zenodo open repository.
Searches and retrieves experimental high-energy physics data tables and cross-section measurements from the HEPData repository.
Builds and optimizes data processing pipelines, integrations, and machine learning scenarios within the SAP Data Intelligence Cloud environment.
Integrates SAP AI Core and Generative AI Hub capabilities into JavaScript and Java applications with enterprise-grade orchestration and security features.
Develops and deploys in-database machine learning models using the SAP HANA Python Client for PAL, APL, and AutoML workflows.
Simplifies LLM API integration by providing a unified Python interface for over 100 providers using a consistent OpenAI-compatible format.
Deploys and manages enterprise AI/ML workloads, Generative AI Hub models, and orchestration pipelines on SAP BTP.
Diagnoses and resolves common ComfyUI execution errors, performance bottlenecks, and configuration issues.
Generates and manages high-fidelity Z-Image text-to-image workflows for ComfyUI using RedCraft and Turbo models.
Orchestrates end-to-end machine learning workflows using industry-standard tools like Airflow, Kubeflow, and MLflow.
Provides precise configuration parameters and compatibility rules for Stable Diffusion, Flux, and video generation models within ComfyUI.
Generates interactive visualizations and comprehensive evaluation reports from LLM social research experiments.
Manages and validates ontology term references for the Dismech knowledge base using the Ontology Access Kit.
Optimizes Haystack RAG pipelines by leveraging DSPy's data-driven prompt tuning and programmatic optimization capabilities.
Maps over 130 Python scientific libraries to their high-performance, native Julia equivalents for bioinformatics, chemistry, and quantum research.
Deploys production-ready recommendation architectures featuring multi-tier caching, feature stores, and automated A/B testing frameworks.
Bridges the gap between Python and Julia ecosystems by providing direct package mappings for 137 high-density scientific AI and data science skills.
Simplifies the installation, configuration, and management of Mozilla Llamafile for running local, OpenAI-compatible LLMs.
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