发现data science & ml类别的 Claude 技能。浏览 61 个技能,找到适合您 AI 工作流程的完美功能。
Analyzes complex chemical processes and molecular structures using rigorous scientific principles and analytical techniques.
Applies rigorous historical methodologies and temporal frameworks to analyze events, identify long-term patterns, and contextualize contemporary trends.
Analyzes global events and policy changes using established political science frameworks and theoretical models.
Retrieves and verifies temporally-accurate data from dynamic machine learning leaderboards to ensure model rankings and benchmark results are current and valid.
Calculates precise token counts for datasets by systematically identifying relevant text fields and applying correct domain filtering logic.
Migrates legacy Python 2 scientific computing code to Python 3 using modern libraries like pandas, numpy, and pathlib.
Analyzes global events, policy changes, and power dynamics using established political science frameworks and international relations theories.
Performs advanced astronomical data analysis, coordinate transformations, and cosmological calculations using the industry-standard Astropy library.
Enables advanced molecular modeling, chemical property calculation, and structural analysis within Python workflows.
Builds and deploys machine learning models for complex time series tasks like forecasting, classification, and anomaly detection.
Manages large-scale N-dimensional arrays with chunking and compression for high-performance scientific computing and cloud storage.
Optimizes the creation of prompts and agent instructions by applying advanced prompt engineering standards and structural patterns.
Applies machine learning to chemistry, biology, and materials science to predict molecular properties and design new compounds.
Executes autonomous multi-step biomedical research tasks including genomics analysis, drug discovery, and clinical interpretation.
Provides programmatic access to over 40 bioinformatics web services for biological data retrieval, identifier mapping, and pathway analysis.
Manipulates and manages AnnData objects for single-cell genomics workflows, including scRNA-seq data processing and file management.
Queries ChEMBL's vast database of bioactive molecules and drug discovery data for medicinal chemistry research.
Processes mass spectrometry data for proteomics and metabolomics analysis using the pyOpenMS library.
Automates the creation of professional PDF documents, reports, and invoices using the robust ReportLab Python toolkit.
Queries the NHGRI-EBI GWAS Catalog for genetic variants, SNP-trait associations, and summary statistics to support genetic epidemiology research.
Accesses the world's largest chemical database to retrieve compound properties, structures, and bioactivity data for cheminformatics workflows.
Predicts high-accuracy 3D binding poses for protein-ligand complexes using diffusion-based deep learning models.
Accesses the Human Metabolome Database to retrieve detailed chemical, clinical, and biological data for over 220,000 metabolites.
Performs comprehensive survival analysis and time-to-event modeling using the scikit-survival Python library.
Streamlines genomics data analysis and pipeline development on the DNAnexus cloud platform using the dxpy SDK and CLI tools.
Analyzes and visualizes high-throughput sequencing data for genomics research and quality control.
Implements standalone command-line inference tools in C, C++, and Rust by extracting weights and logic from PyTorch models without Python dependencies.
Queries the Ensembl REST API to retrieve genomic annotations, sequences, variants, and comparative genomics data for over 250 species.
Simplifies molecular cheminformatics workflows by providing a Pythonic interface for RDKit with sensible defaults and parallel processing.
Provides structured guidance for video analysis, motion detection, and temporal event tracking using computer vision techniques.
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