Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Build and automate end-to-end MLOps pipelines from data preparation and model training to production deployment.
Implements high-performance vector similarity search and RAG retrieval patterns using popular vector databases and indexing strategies.
Trains and deploys complex neural networks across distributed E2B sandbox environments using custom architectures or pre-built templates.
Builds sophisticated Retrieval-Augmented Generation (RAG) systems to ground LLM responses in external knowledge bases and private documentation.
Automates professional-grade spreadsheet creation, financial modeling, and data analysis with formula preservation and industry-standard formatting.
Combines vector similarity and keyword-based search to improve retrieval accuracy and recall in RAG systems.
Calculates comprehensive portfolio risk metrics and performance indicators to enhance financial risk management and reporting.
Implements advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production applications.
Defines robust Pydantic data models for structured RAG pipeline configurations and metadata validation.
Orchestrates complex multi-agent systems using specialized patterns for dynamic reasoning and deterministic workflows.
Implements asymmetric embedding strategies to improve vector search accuracy by distinguishing between document ingestion and user queries.
Implements Retrieval-Augmented Generation (RAG) using the Vertex AI Engine to ground agent responses in private data sources.
Implements Vertex AI RAG Engine patterns for grounding AI agents with private data sources and verifiable citations.
Accelerates Google Agent Development Kit (ADK) projects with standardized environment setup, Vertex AI configuration, and robust agent scaffolding.
Streamlines the creation and configuration of production-grade AI agents using the Google Agent Development Kit (ADK) and Vertex AI.
Synthesizes multi-source research findings into a unified, evidence-graded report with proactive conflict resolution.
Enhances retrieval-augmented generation processes with query expansion, multi-query retrieval, and mandatory source citations.
Simplifies Gemini model configuration and implementation using the Google Cloud Vertex AI SDK.
Transforms raw instructions into structured, production-ready prompts using advanced prompt engineering frameworks and Claude-specific best practices.
Configures and implements Google Vertex AI SDK patterns for Gemini models including safety settings, streaming, and function calling.
Optimizes document chunking and embedding workflows for high-performance RAG systems using Vertex AI.
Generates comprehensive multi-LLM research strategies and model-optimized prompts for systematic analysis and strategic planning.
Optimizes Retrieval-Augmented Generation (RAG) pipelines using advanced re-ranking, query expansion, and semantic caching techniques.
Optimizes AI agent behavior using structured XML system prompts, few-shot examples, and clear instruction hierarchies.
Automates the creation, management, and deletion of RAG corpora specifically for the Vertex AI RAG Engine.
Implements robust document attribution and Retrieval-Augmented Generation (RAG) patterns for verifiable AI responses.
Verifies causal narratives between natural gas price surges and fertilizer market disruptions using automated statistical analysis.
Builds structured data pipelines, SQL queries, and AI agents using the Oxy framework's hierarchical logic.
Performs automated exploratory data analysis and generates detailed reports for over 200 scientific file formats across multiple domains.
Analyzes legacy Thai DBF accounting databases by converting them to Parquet for high-performance DuckDB querying.
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