Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Optimizes vector search and RAG applications through intelligent embedding model selection and advanced document chunking strategies.
Builds, trains, and optimizes hybrid quantum-classical models using automatic differentiation and hardware-agnostic circuit programming.
Generates high-quality statistical graphics and data visualizations with seamless Pandas integration.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production environments.
Implements comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking frameworks.
Implement comprehensive evaluation frameworks for AI applications using automated metrics, human feedback, and LLM-as-judge patterns.
Manages large-scale N-dimensional arrays with chunked storage, compression, and seamless cloud integration for scientific computing pipelines.
Empowers Claude to perform advanced time series machine learning, including classification, forecasting, and anomaly detection using the specialized aeon toolkit.
Optimizes vector database performance by tuning HNSW parameters and implementing advanced quantization strategies for AI applications.
Optimizes text embedding selection and chunking strategies to enhance semantic search and RAG application performance.
Architects and implements sophisticated LLM applications using LangChain agents, chains, and memory patterns.
Creates, edits, and analyzes sophisticated Excel workbooks with a focus on dynamic formulas, financial modeling standards, and automated recalculation.
Accesses and queries the PubMed database for biomedical literature, systematic reviews, and citation management.
Calculates comprehensive portfolio risk metrics and risk-adjusted return ratios for quantitative trading strategies.
Combines vector similarity and keyword-based search to improve retrieval accuracy and recall in AI-driven applications.
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.
Provides expert guidance for conducting and reviewing Simulated Treatment Comparisons (STC) following biostatistical best practices and NICE standards.
Facilitates the configuration, performance optimization, and operational management of Templar AI miners within the Bittensor decentralized training network.
Implements comprehensive evaluation frameworks for LLM applications using automated metrics, human-in-the-loop feedback, and A/B testing.
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.
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