Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Generates interactive, publication-quality Python charts and dashboards for data exploration and presentation.
Optimizes LLM performance and reliability through advanced prompting techniques like few-shot learning and chain-of-thought reasoning.
Develops and trains Graph Neural Networks (GNNs) for node classification, link prediction, and geometric deep learning tasks.
Orchestrates end-to-end MLOps pipelines from data preparation and model training to production deployment and monitoring.
Designs and implements sophisticated LLM applications using the LangChain framework for complex AI workflows.
Conducts systematic, high-rigor research and data synthesis to transform raw information into actionable insights and structured reports.
Implements and trains advanced reinforcement learning algorithms to create autonomous agents that evolve through experience.
Builds, evaluates, and deploys production-ready machine learning models using the industry-standard scikit-learn library.
Trains and deploys complex neural network architectures within distributed E2B sandbox environments for scalable machine learning workflows.
Explains machine learning model predictions and feature importance using SHAP values and comprehensive visualizations.
Implements robust Bayesian survival analysis models including Weibull and Cox-like piecewise hazards with censoring support.
Accelerates data manipulation and ETL pipelines with the high-performance Polars DataFrame library.
Creates, edits, and analyzes Excel spreadsheets with professional formatting, automated formula recalculation, and integrated data visualization.
Implements robust Bayesian meta-analysis models using Stan and JAGS to synthesize data across multiple studies with advanced statistical precision.
Builds and optimizes Retrieval-Augmented Generation (RAG) systems using advanced vector search, semantic chunking, and retrieval patterns.
Implements high-performance adaptive learning and memory distillation for self-improving AI agents using AgentDB.
Queries the Federal Reserve Economic Data (FRED) API to retrieve over 800,000 economic time series for financial research and macroeconomic analysis.
Evaluates and benchmarks different embedding models to optimize semantic search and vector retrieval performance on your specific data.
Streamlines the creation, fitting, and validation of Bayesian models using PyMC's modern probabilistic programming interface.
Designs, simulates, and executes quantum circuits using Google's Cirq framework for NISQ-era hardware and noise-aware algorithms.
Provides programmatic access to global statistical data for demographic, economic, and environmental research.
Automates the end-to-end scientific research pipeline from hypothesis generation and data analysis to publication-ready LaTeX manuscripts.
Automates protein testing and validation through a cloud-based laboratory platform for accelerated biotechnological research and sequence optimization.
Orchestrates the development of complete, production-ready Claude Code agents using Anthropic's official best practices for context engineering and tool design.
Accesses AI-ready drug discovery datasets and benchmarks for therapeutic machine learning and pharmacological prediction.
Retrieves nucleotide sequences, raw sequencing reads, and metadata from the European Nucleotide Archive for genomics research.
Deploys and optimizes fine-tuned LLMs using native Unsloth kernels, vLLM, or SGLang for high-performance production serving.
Creates, edits, and analyzes professional Excel workbooks with dynamic formulas, automated recalculation, and industry-standard formatting.
Deploys and runs Python applications on serverless cloud infrastructure with automatic scaling and GPU acceleration.
Processes and analyzes whole-slide pathology images using advanced machine learning, spatial graph construction, and multiparametric imaging workflows.
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