Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Manages local and self-hosted vector embeddings for RAG-based AI applications and semantic search.
Orchestrates over 48 specialized AI agents for autonomous cryptocurrency trading, market analysis, and backtesting across multiple exchanges.
Queries the ClinicalTrials.gov API v2 to search, retrieve, and analyze clinical trial data for research and patient matching.
Queries and analyzes over 240 million scholarly works, authors, and institutions via the OpenAlex API.
Performs comprehensive single-cell RNA-seq analysis including quality control, clustering, and cell type annotation using the Scanpy framework.
Generates interactive, publication-quality data visualizations and dashboards using the Plotly Python library.
Provides programmatic access and comprehensive analysis of the DrugBank database for pharmaceutical research and bioinformatics workflows.
Searches the arXiv preprint repository for scholarly articles in computer science, physics, mathematics, and quantitative biology.
Provides specialized algorithms and workflows for advanced time series tasks including forecasting, classification, and anomaly detection.
Automates life sciences research data management by integrating Claude with the Benchling R&D platform's registry, inventory, and notebooks.
Simulates and analyzes open and closed quantum mechanical systems using the QuTiP Python library.
Queries the ClinicalTrials.gov API to search for medical studies, retrieve trial details, and export structured clinical research data.
Searches the arXiv preprint repository for scholarly articles across various scientific and technical domains.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank, including drug properties, interactions, targets, and chemical structures.
Designs, simulates, and executes quantum circuits on simulators and real quantum hardware using Google's Cirq framework.
Accelerates scientific discovery by automating the generation, refinement, and testing of research hypotheses using large language models and observational datasets.
Generates publication-quality scientific visualizations and data plots locally using Python's Matplotlib and Seaborn libraries.
Builds high-performance Retrieval-Augmented Generation systems using vector databases, semantic search, and advanced retrieval patterns.
Queries the Ensembl REST API to retrieve gene annotations, sequences, variants, and comparative genomics data for over 250 species.
Builds end-to-end MLOps pipelines for data preparation, model training, validation, and production deployment.
Processes and analyzes comprehensive physiological signals including ECG, EEG, and EDA for psychophysiology and clinical research.
Trains and deploys sophisticated neural network architectures across distributed E2B sandbox environments.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank including drug properties, interactions, and molecular structures.
Processes and analyzes physiological signals like ECG, EEG, and EDA using the NeuroKit2 Python library.
Builds end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment.
Automates the end-to-end scientific research lifecycle from data analysis and hypothesis generation to publication-ready LaTeX manuscripts.
Implements comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Integrates Reactome's open-source curated pathway database for biological pathway analysis, gene mapping, and systems biology research.
Generates rigorous, testable scientific hypotheses and detailed experimental designs based on observations and existing literature.
Generates professional, multi-page PDF reports with formatted text, tables, and embedded visualizations using the ReportLab library.
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