Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Extracts text, tables, and metadata from PDF, DOCX, and HTML documents to power RAG pipelines and data processing workflows.
Integrates ElevenLabs Scribe v1 for high-accuracy speech-to-text transcription across 99 languages with speaker diarization.
Streamlines the integration and testing of Gemma 3 270M models within the Claude Code environment.
Implements production-ready RAG pipelines and advanced retrieval strategies using LlamaIndex templates and scripts.
Architects scalable AI memory systems with optimized retention, storage backends, and multi-level context patterns.
Standardizes the implementation of Claude-powered AI assistants across the Insight Business Suite with built-in persona systems and BYOK management.
Implements and benchmarks advanced document chunking strategies to optimize retrieval performance and context preservation in RAG pipelines.
Configures cloud GPU environments and provides selection guidance for Modal, Lambda Labs, and RunPod platforms.
Implements intelligent model routing strategies to optimize for cost, performance, and reliability when building AI applications with OpenRouter.
Deploys machine learning models into full-stack applications using production-ready FastAPI endpoints, Next.js UI components, and Supabase schemas.
Automates the end-to-end Support Vector Machine (SVM) workflow for linear and non-linear classification tasks within Teradata Vantage.
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.
Simplifies the creation and review of Bayesian models using BUGS and JAGS declarative syntax and precision parameterization.
Analyzes machine learning training logs to visualize loss curves, detect training issues, and provide diagnostic insights.
Integrates Google Gemini's native vision capabilities to analyze, summarize, and extract structured data from complex PDF documents.
Guides the implementation and review of Simulated Treatment Comparisons (STC) using NICE DSU TSD 18 compliant methodologies.
Facilitates the creation, review, and optimization of Bayesian models using PyMC 5 and ArviZ diagnostics.
Implements sophisticated persistent memory systems to help AI assistants retain context and user information across multiple interactions.
Provides expert guidance and best practices for conducting Matching-Adjusted Indirect Comparisons (MAIC) in biostatistical research.
Manages fast, reproducible scientific Python environments by unifying the conda and PyPI ecosystems using the Rust-based Pixi tool.
Optimizes LLM interactions through advanced prompting techniques like few-shot learning, chain-of-thought, and systematic template design.
Integrates multiple academic databases including PubMed, Semantic Scholar, and OpenAlex for comprehensive literature reviews and full-text retrieval.
Enforces production-grade Python standards by eliminating generic AI coding patterns through PEP 8 compliance, rigorous type hinting, and pandas best practices.
Streamlines academic research data analysis by enforcing reproducible dbt pipelines and interactive Streamlit dashboards.
Automates the creation, modification, and analysis of professional spreadsheets with a focus on dynamic formulas and industry-standard financial modeling.
Converts Excel (.xlsx) spreadsheets into clean Markdown tables for seamless data analysis and documentation.
Streamlines feature engineering in R using standardized preprocessing patterns for the recipes package.
Generates high-conviction trading signals and technical analysis reports using multi-indicator market scanning.
Automates the creation, editing, and analysis of professional Excel spreadsheets with dynamic formulas and industry-standard formatting.
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