Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Implements production-grade LLM-as-a-Judge techniques for evaluating AI outputs through rigorous scoring, pairwise comparisons, and bias mitigation.
Powers probabilistic fund performance modeling through graduation rates, multi-MOIC analysis, and Monte Carlo simulations.
Optimizes venture capital reserve allocations and follow-on investment strategies within the Phoenix fund model.
Integrates Alpha Vantage APIs to fetch real-time and historical market data, technical indicators, and financial fundamentals.
Streamlines the development of Python workflows using Awkward Array for jagged, nested, and record-based data structures.
Implement efficient vector-based similarity search, semantic retrieval, and RAG patterns across major vector databases.
Proposes structured, data-driven experiment plans by analyzing historical training reports, logs, and research goals.
Optimizes long-running AI agent sessions by implementing structured context compression to maintain technical accuracy and memory efficiency.
Integrates Claude with the FinnHub API to retrieve real-time stock quotes, fundamental data, crypto prices, and market news.
Implements production-grade prompt engineering patterns, RAG optimization, and agentic system architectures for advanced AI products.
Empowers autonomous AI agents with real-time X (Twitter) search, web search, and sandboxed Python code execution capabilities.
Implements comprehensive evaluation frameworks for LLM applications using automated metrics, human-in-the-loop feedback, and A/B testing.
Processes and analyzes billion-row tabular datasets using lazy, out-of-core DataFrame operations without exceeding available RAM.
Transforms raw data into persuasive narratives and visualizations for business stakeholders and executive presentations.
Optimizes Apache Spark performance through advanced partitioning, memory tuning, and shuffle management strategies.
Implements and optimizes text embedding models and chunking strategies for high-performance semantic search and RAG applications.
Build robust Retrieval-Augmented Generation systems for LLM applications using vector databases and semantic search.
Builds a unified abstraction layer for integrating and switching between multiple LLM providers in Rails applications.
Optimizes vector database performance by tuning HNSW parameters, quantization strategies, and memory usage for high-scale search applications.
Verifies mathematical derivations step-by-step by checking algebra, index consistency, and dimensional accuracy.
Logs machine learning experiments with hyperparameters, metrics, and visualizations for systematic research tracking.
Architects sophisticated LLM applications using agents, memory, and tool integration within the LangChain framework.
Orchestrates end-to-end MLOps pipelines from data preparation and model training to production deployment and monitoring.
Generates and optimizes ServiceX queries in func_adl for analyzing ATLAS xAOD high-energy physics data.
Standardizes Python experiment layouts, stage entrypoints, and asset handling for consistent data science workflows.
Builds robust, production-grade backtesting systems for trading strategies while eliminating common statistical biases.
Queries the Reactome REST API to perform pathway enrichment analysis, gene mapping, and systems biology research directly within Claude.
Calculates comprehensive portfolio risk metrics like VaR, CVaR, and Sharpe ratios to monitor and manage financial exposure.
Integrates Google Gemini's advanced multimodal capabilities to process, analyze, and generate audio, video, images, and documents directly within your development workflow.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production.
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