Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Challenges mainstream assumptions and identifies project blind spots by uncovering counter-evidence through deep academic and web research.
Provides rigorous, conference-grade peer reviews for machine learning research papers targeting NeurIPS and ICML standards.
Conducts deep comparative research against State-of-the-Art (SOTA) works to define and position project contributions.
Generates engineering-focused research proposals by validating academic literature against practical implementation constraints.
Orchestrates machine learning experiments by monitoring GPU availability and dynamically dispatching tasks to remote infrastructure.
Conducts systematic literature reviews by synthesizing data from arXiv, Google Scholar, bioRxiv, and general web searches.
Orchestrates and executes machine learning experiments on remote servers using local Claude or Codex agents.
Facilitates rigorous experimental design and ensures data reproducibility by integrating academic research tools into AI workflows.
Streamlines AI-native application development by providing expert patterns for Weaviate vector search, RAG pipelines, and multi-tenancy.
Integrates real-time web search and grounded AI responses into applications using the Perplexity Sonar API.
Simplifies the development of AI-powered applications using the OpenAI SDK and the GPT-5 model family.
Builds stateful, multi-agent applications and cyclic AI workflows using LangGraph for complex orchestration and persistent state management.
Migrates codebases and prompts from earlier Claude models to Opus 4.5 by automating model string updates and behavioral adjustments.
Analyzes raw interaction logs to extract recurring behavioral patterns and refine AI decision-making.
Generates and optimizes high-performance prompts for Claude, GPT, and other LLMs using research-backed engineering techniques.
Enables Claude to analyze, transcribe, and generate multimedia content including audio, images, videos, and documents through the Gemini API.
Develops, tests, and deploys healthcare AI models using clinical data and specialized medical coding systems.
Automates end-to-end empirical data analysis workflows using Stata and R for publication-ready research output.
Audits R projects against UK Government Reproducible Analytical Pipelines (RAP) maturity standards to ensure code quality and transparency.
Performs diffusion-based molecular docking to predict high-accuracy 3D binding poses between proteins and ligands for drug discovery.
Calculates advanced economic statistics and estimates using specialized R methodologies for weighted and bunched data.
Provides comprehensive technical specifications and implementation patterns for Google's Veo 3.1 video generation model.
Analyzes, summarizes, and documents robot learning experiment runs across local and cluster environments.
Manages local GGUF model inference and API serving through llama.cpp within worker terminals.
Fetches official, up-to-date documentation and code examples for the R Tidyverse ecosystem.
Interprets, generates, and captions publication-quality scientific figures for quantitative academic research.
Automates the transition from literature review to experimental design by analyzing academic papers and proposing novel research methods.
Queries official R Shiny framework documentation to build, debug, and deploy interactive web applications.
Accesses real-time R package documentation, vignettes, and task views across CRAN, tidyverse, and Bioconductor ecosystems.
Generates publication-ready methods and results sections for clinical prediction and machine learning papers using TRIPOD+AI standards.
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