Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Accesses global statistical data from Data Commons for demographic, economic, and environmental analysis.
Performs advanced statistical hypothesis testing, regression analysis, and Bayesian modeling with automated assumption checking and APA-style reporting.
Evaluates scientific manuscripts and grant proposals using a systematic toolkit for methodology, statistics, and reporting standards.
Performs comprehensive exploratory data analysis and generates detailed reports for over 200 scientific file formats.
Converts chemical structures into machine learning-ready numerical representations using over 100 specialized featurizers and pretrained embeddings.
Creates publication-quality statistical graphics and exploratory data visualizations using a high-level Python interface.
Performs complex astronomical data analysis and astrophysical calculations using the comprehensive Astropy Python library.
Generates testable, evidence-based scientific hypotheses and structured experimental designs to accelerate autonomous discovery.
Processes and analyzes mass spectrometry data using Python-based spectral similarity, metadata harmonization, and data filtering tools.
Streamlines deep learning development by organizing PyTorch code into scalable, high-performance Lightning modules and data pipelines.
Manages large-scale N-dimensional arrays with chunking, compression, and cloud-native storage for scientific computing.
Streamlines the development, deployment, and management of bioinformatics pipelines and data on the DNAnexus cloud genomics platform.
Performs comprehensive survival analysis and time-to-event modeling using the scikit-survival library in Python.
Implements comprehensive machine learning workflows using scikit-learn, covering data preprocessing, model training, evaluation, and pipeline deployment.
Accesses the world's leading protein sequence and functional information resource via the UniProt REST API.
Provides comprehensive Python tools for biological computation, sequence analysis, and bioinformatics database access.
Detects system hardware capabilities and provides optimized computational strategies for scientific and data-intensive tasks.
Empowers Claude to create, analyze, and format professional Excel spreadsheets and financial models with automated formula recalculation.
Accesses NIH Metabolomics Workbench to query over 4,200 studies, metabolite structures, and standardized biochemical nomenclature.
Explores and maps complex codebases using AST analysis to reduce token usage by 95% while maintaining structural visibility.
Generates publication-quality scientific diagrams, neural network architectures, and flowcharts using specialized Python libraries.
Accesses the Reactome database to perform biological pathway analysis, gene mapping, and enrichment studies for systems biology.
Facilitates programmatic access to the ClinicalTrials.gov API v2 for advanced trial discovery, patient matching, and medical research data extraction.
Implements high-performance reinforcement learning training, custom environments, and optimized vectorization for parallel simulations.
Builds and deploys production-grade bioinformatics pipelines as serverless workflows on the Latch platform.
Facilitates creative scientific problem-solving by generating hypotheses and exploring interdisciplinary connections as a research ideation partner.
Manipulates, extracts, and generates PDF documents using specialized Python libraries and command-line tools for automated document workflows.
Searches and retrieves life sciences preprints from the bioRxiv database by keywords, authors, and categories.
Accesses and analyzes over 240 million scholarly works, authors, and institutions via the OpenAlex API for automated scientific discovery.
Empowers Claude to perform graph-based drug discovery, molecular property prediction, and protein modeling using the TorchDrug framework.
Scroll for more results...