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。
Systematically refines and validates research tools through multi-phase iterative testing and rigorous data-driven evaluation.
Facilitates exploratory abductive reasoning and hypothesis testing through interactive REPL environments.
Facilitates structured, step-by-step thinking for complex analytical decisions and qualitative research framework development.
Powers iterative hypothesis testing and exploratory abductive inference through an interactive REPL environment.
Initializes qualitative research projects through a Socratic onboarding process that establishes philosophical foundations and methodological frameworks.
Ensures methodological rigor by aligning philosophical assumptions, language usage, and analytical practices in AI-assisted research.
Implements a compositional AI framework based on category theory and GF(3) triadic balance for deterministic, self-modifying agent architectures.
Validates alignment between research epistemology, ontology, and analytical practice to ensure rigorous qualitative research outcomes.
Constructs and validates rigorous three-level Gioia methodology hierarchies for qualitative data analysis and academic publication.
Enforces methodological rigor in AI-assisted qualitative research through automated rule generation, saturation tracking, and analytical branching.
Resolves conflicting research patterns and theoretical tensions using contemplative, non-dual reasoning frameworks.
Constructs, validates, and exports hierarchical data structures for qualitative research using the Gioia methodology.
Converts audio recordings, PDFs, and diverse document formats into structured markdown for qualitative research and AI analysis.
Deploys and trains advanced reinforcement learning algorithms for autonomous agents to optimize behavior through experience.
Orchestrates systematic document coding for qualitative research through automated batch processing and audit trail generation.
Converts audio recordings, PDFs, and diverse document formats into structured markdown for qualitative research and AI-assisted analysis.
Captures and stores failed Hotvect command invocations as executable shell scripts for seamless debugging and reproduction.
Automates the retrieval of training and test data dependencies from S3 for local machine learning model development and backtesting.
Performs specialized time series machine learning tasks including classification, forecasting, and anomaly detection using scikit-learn compatible algorithms.
Streamlines the configuration and validation of Hotvect algorithm training runs for Vowpal Wabbit.
Provides comprehensive tools for astronomical data analysis, including coordinate transformations, unit conversions, and FITS file manipulation.
Builds and trains machine learning models on genomic interval data to generate embeddings for regions, single cells, and metadata.
Performs advanced molecular analysis, descriptor calculation, and chemical informatics using the RDKit library.
Automates the retrieval of SageMaker backtest results from Amazon S3 for local analysis and performance comparison.
Provides PhD-level guidance on research ethics, IRB compliance, and data privacy analysis for study protocols and algorithmic models.
Automates the creation of robust data cleaning and preprocessing pipelines for Python-based data science workflows.
Standardizes variable summation and entity aggregation within the PolicyEngine microsimulation framework.
Builds and validates the three-level Gioia data structure for systematic qualitative research analysis and academic publication.
Provides foundational mathematical tools and statistical methods for data analysis, hypothesis testing, and machine learning architecture.
Automates production-grade ETL pipelines and data orchestration using industry-standard tools like Airflow, dbt, and Prefect.
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