Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Configures and verifies scientific data acquisition systems by automating hardware discovery and parameter management.
Architects complex multi-agent systems and workflows using standardized patterns across major AI frameworks.
Implements high-performance adaptive learning and memory distillation for AI agents using the AgentDB vector backend.
Implements adaptive learning and meta-cognitive capabilities for AI agents to optimize strategies based on historical experience.
Conducts rigorous, publication-quality quantitative research and statistical analysis using Stata through a systematic phased workflow.
Automates the translation of MetaTrader 5 (MQL5) indicators into validated Python implementations for algorithmic trading.
Automates experiment tracking and backtest logging using the MLflow Python API and QuantStats metrics.
Optimizes AI outputs using research-backed prompting techniques to increase response quality and accuracy by up to 115%.
Enhances AI response quality by 45-115% using research-backed techniques like monetary framing, expert personas, and step-by-step reasoning.
Simplifies Large Language Model integration by providing expert guidance on transformer architecture, tokenization, and inference optimization.
Measures and optimizes Large Language Model performance through systematic quality frameworks, benchmarks, and hallucination detection.
Adapts and optimizes Large Language Models using LoRA, QLoRA, and instruction tuning for domain-specific applications.
Deploys and optimizes large language models using production-grade frameworks like vLLM, TGI, and FastAPI.
Builds production-grade Retrieval Augmented Generation pipelines with vector search, hybrid retrieval, and advanced re-ranking strategies.
Optimizes vector storage and retrieval strategies for high-performance AI applications and semantic search.
Develops autonomous AI agents and multi-agent systems using industry-standard frameworks like LangChain, CrewAI, and AutoGen.
Optimizes Large Language Model performance through expert prompt design, few-shot learning, and advanced reasoning patterns.
Trains and deploys complex neural networks across distributed E2B sandbox environments directly within Claude.
Implements high-performance adaptive learning and experience replay for AI agents using AgentDB's ultra-fast vector storage.
Implements high-performance persistent memory and learning patterns for AI agents using AgentDB.
Deploys and manages cloud-based AI agent swarms using event-driven workflow automation and intelligent coordination.
Generates structured plans to decompose complex AI include chains into modular, reusable components.
Integrates Guerino Mazzola's Topos of Music framework to enable categorical music analysis and mathematical composition.
Integrates Guerino Mazzola's mathematical music theory and the Topos of Music framework into Claude for advanced computational composition.
Provides standardized C++20 implementations for high-performance numerical computing, matrix operations, and parallel I/O.
Accesses and retrieves nucleotide sequences, raw reads, and genome assemblies from the European Nucleotide Archive (ENA) via REST APIs and FTP.
Transforms vague research interests into concrete, actionable, and tractable research questions with a systematic feasibility analysis.
Builds, evaluates, and deploys code-first AI agents and multi-agent systems using Google's Agent Development Kit.
Guides developers through the methodical, step-by-step implementation of research papers to ensure deep understanding and reproducible results.
Generates optimized race-day pacing and fueling strategies tailored to individual fitness levels and specific course topography.
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