Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Streamlines the creation and debugging of data preprocessing pipelines for BayesFlow simulation-based inference.
Standardizes tensor operations using Keras 3 backend-agnostic math to ensure compatibility across PyTorch, JAX, and TensorFlow.
Enforces best practices for BayesFlow extension packages, including src-layout, dependency management, and API exports.
Automates the configuration of MLflow and Weights & Biases to track machine learning parameters, metrics, and artifacts.
Converts audio and video files into accurate text transcripts with precise word-level timestamps using WhisperX.
Analyzes and extracts insights from images, videos, and audio files using advanced AI models.
Transforms raw CSV data into interactive Plotly visualizations, comprehensive statistical reports, and professional multi-plot dashboards.
Generates comprehensive business performance reports and strategic recommendations from sales and revenue data.
Optimizes vector search performance and resource efficiency for production-scale LLM applications.
Optimizes vector search and RAG applications by implementing advanced embedding model selection and chunking strategies.
Implements robust data validation and quality assurance using Great Expectations, dbt tests, and data contracts.
Streamlines academic literature review and research paper discovery with automated prioritization and screening workflows.
Build and automate end-to-end MLOps pipelines from data preparation and model training to production deployment.
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.
Orchestrates complex multi-agent systems using specialized patterns for dynamic reasoning and deterministic workflows.
Implements Retrieval-Augmented Generation (RAG) using the Vertex AI Engine to ground agent responses in private data sources.
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.
Optimizes document chunking and embedding workflows for high-performance RAG systems using Vertex AI.
Streamlines the creation and debugging of BayesFlow data preprocessing pipelines for simulation-based inference.
Optimizes GPU memory usage and automates recovery from CUDA out-of-memory errors during BayesFlow training.
Generates publication-ready scientific diagrams and statistical plots for academic papers using a multi-agent pipeline.
Automates PDF manipulation and generates publication-quality scientific diagrams for advanced technical documentation.
Analyzes experimental results from a positive perspective to identify growth opportunities and successful patterns.
Evaluates the internal validity, external validity, and reproducibility of experimental methodologies within research and data science workflows.
Refines technical hypotheses and proposes strategic modifications based on experimental outcomes and system data.
Generates rigorous, reproducible experimental plans and resolves GPU infrastructure issues for data science workflows.
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