Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Manages large-scale N-dimensional arrays with chunked storage, compression, and seamless cloud integration for scientific computing pipelines.
Implement comprehensive evaluation frameworks for AI applications using automated metrics, human feedback, and LLM-as-judge patterns.
Implements comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking frameworks.
Provides specialized technical auditing and compliance reviews for Physics-Guided GNN research papers targeting IEEE Power & Energy Society submissions.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production environments.
Generates high-quality statistical graphics and data visualizations with seamless Pandas integration.
Optimizes vector database performance by tuning HNSW parameters, quantization strategies, and scaling configurations for high-efficiency similarity search.
Builds, trains, and optimizes hybrid quantum-classical models using automatic differentiation and hardware-agnostic circuit programming.
Implements robust multi-agent systems using Pydantic tool schemas, state management, and advanced orchestration patterns.
Optimizes Text-to-Speech model training and voice cloning using the Unsloth library for faster performance and lower VRAM usage.
Designs and implements sophisticated LLM applications using LangChain 1.x and LangGraph for advanced agentic workflows and state management.
Automates the creation, editing, and analysis of complex Excel spreadsheets with support for dynamic formulas and financial modeling standards.
Optimizes vector search and RAG applications through intelligent embedding model selection and advanced document chunking strategies.
Automates professional spreadsheet creation, financial modeling, and data analysis with dynamic formulas and industry-standard formatting.
Builds process-based discrete-event simulations in Python to model complex systems with resource contention and time-based events.
Performs precise unit conversions, dimensional analysis, and unit-aware arithmetic using the Pint library.
Transforms monolithic Python research code and notebooks into modular, production-ready package structures.
Transforms chemical structures into machine learning-ready numerical features using a library of over 100 featurizers and pretrained models.
Optimizes LLM performance and reliability through automated model selection, cost estimation, and intelligent fallback strategies.
Generates comprehensive loyalty program performance reports and data-driven growth projections via Metabase integration.
Manages, analyzes, and visualizes multi-modal spatial omics data using the SpatialData Python ecosystem and OME-NGFF standards.
Evaluates scientific research rigor and evidence quality using standardized frameworks like GRADE and Cochrane.
Manages and analyzes microscopy data through the OMERO Python API for scientific imaging and high-content screening workflows.
Provides comprehensive tools for phylogenetic tree manipulation, evolutionary analysis, and high-quality biological data visualization.
Streamlines deep learning development by organizing PyTorch code into scalable, boilerplate-free Lightning modules and automated training workflows.
Builds and orchestrates end-to-end MLOps pipelines from data preparation through production model deployment.
Performs high-performance, vectorized string manipulation and text cleaning using NumPy's specialized string modules.
Implement and automate comprehensive evaluation strategies for Large Language Model applications using metrics, human feedback, and LLM-as-judge patterns.
Provides direct access to the KEGG REST API for biological pathway analysis, gene mapping, and metabolic research.
Integrates Google Gemini's multimodal analysis, massive context processing, and image generation capabilities directly into Claude Code.
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