Descubre Habilidades de Claude para data science & ml. Explora 71 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Designs and implements sophisticated LLM applications using LangChain's framework for agents, memory, and complex workflows.
Architects sophisticated LLM applications using the LangChain framework to implement agents, memory management, and complex workflow chains.
Builds robust Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search to ground AI responses in proprietary knowledge.
Implements advanced prompt engineering techniques to optimize LLM performance, reliability, and structured output in production environments.
Implements rigorous evaluation strategies for LLM applications using automated metrics, human-in-the-loop feedback, and systematic benchmarking.
Manages complex Excel workbooks with automated formula recalculation, professional financial modeling standards, and deep data analysis capabilities.
Optimizes LLM interactions through advanced prompting techniques like few-shot learning, chain-of-thought, and systematic template design.
Streamlines the creation, testing, and optimization of sophisticated autonomous agents and subagents within the Claude Code ecosystem.
Generates publication-quality charts and statistical visualizations using Matplotlib and Seaborn.
Automates the creation, formatting, and analysis of professional-grade Excel spreadsheets and financial models.
Implements high-performance persistent memory and reasoning patterns for AI agents using vector storage and reinforcement learning.
Implements adaptive learning and pattern recognition systems to enable AI agents to optimize strategies and improve through experience.
Exports data analysis results into multiple professional formats including CSV, Excel, JSON, and Markdown with customized formatting.
Automates the creation, editing, and analysis of professional-grade Excel spreadsheets and financial models with dynamic formulas and rigorous verification.
Streamlines machine learning model performance assessment in R using the tidymodels ecosystem.
Provides a structured framework for comprehensive data processing, multi-step analysis patterns, and standardized output generation.
Automates the creation, editing, and analysis of professional Excel spreadsheets with advanced formula support and industry-standard financial modeling.
Automates dataset analysis and cleaning by detecting data types, identifying quality issues, and generating Python scripts for standardized data preparation.
Analyzes legacy Thai DBF accounting databases by converting them to Parquet for high-performance DuckDB querying.
Develops, optimizes, and submits high-performance competitive algorithms for Boolean Satisfiability, Vehicle Routing, and Knapsack challenges on The Innovation Game platform.
Generates and validates executable Python behavior trees for robotic systems using natural language task descriptions.
Manages and interacts with Hugging Face Spaces by providing tools to search repositories, retrieve metadata, and control application runtimes.
Interfaces with the Ollama API to perform high-performance text completions and clinical analysis using the Phi-4 language model.
Optimizes the deployment, operation, and performance of Grail miners on Bittensor Subnet 81 for verifiable language model post-training.
Coordinates multiple AI models in parallel to perform comparative analysis, aggregate decision-making, and track performance across diverse LLM providers.
Automates schema validation and business logic extraction to ensure accuracy when generating PySpark ETL transformation code.
Implements comprehensive evaluation frameworks for LLM applications using automated metrics, human feedback, and LLM-as-judge patterns.
Implements advanced LLM prompt engineering techniques to maximize model performance, reliability, and controllability in production applications.
Builds sophisticated LLM applications using LangChain's agents, memory management, and complex chain patterns.
Orchestrates end-to-end machine learning pipelines from data preparation and training to production deployment and monitoring.
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