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。
Implements nine reinforcement learning algorithms to train autonomous agents that improve through experience.
Implements high-performance persistent memory and context management for AI agents using AgentDB and vector storage.
Automates the end-to-end machine learning lifecycle including data preprocessing, model selection, and hyperparameter optimization.
Simulates scholarly peer reviews by grounding critiques in specific theoretical and methodological perspectives retrieved from Zotero.
Synthesizes academic literature corpora into theoretical maps and debate frameworks using Zotero integration.
Guides researchers through systematic, theory-driven qualitative interview analysis to identify anomalies and generate novel theoretical insights.
Conducts systematic qualitative analysis of interview data for sociological research using theory-informed or data-first methodologies.
Generates custom writing skills by performing systematic genre analysis on a corpus of academic article sections.
Accesses and analyzes over 800,000 economic time series from the Federal Reserve Bank of St. Louis.
Queries and downloads large-scale public cancer imaging datasets from the NCI Imaging Data Commons for AI training and medical research.
Provides comprehensive access to the BRENDA enzyme database for retrieving kinetic parameters, reaction stoichiometry, and organism-specific biochemical data.
Generates professional, biomarker-stratified clinical decision support documents and treatment recommendation reports for pharmaceutical and clinical research.
Simulates and analyzes open quantum systems, master equations, and decoherence using the Quantum Toolbox in Python.
Performs advanced numerical computing, matrix operations, and scientific visualization using MATLAB and GNU Octave syntax.
Builds visually engaging, research-backed scientific presentations and slide decks for academic and professional talks.
Generates publication-quality scientific diagrams and architectural schematics using AI-driven iterative refinement.
Facilitates the development and training of quantum machine learning models using automatic differentiation and hybrid quantum-classical workflows.
Extends pandas with spatial operations for managing, analyzing, and visualizing vector geographic data types.
Connects Claude to the K-Dense Web AI co-scientist platform for executing complex, end-to-end scientific research workflows.
Automates the creation, editing, and analysis of professional spreadsheets with support for complex formulas, data visualization, and industry-standard formatting.
Conducts real-time academic and technical research using Perplexity Sonar models via OpenRouter to provide cited findings, statistical data, and deep analytical reasoning.
Automates complex quantum chemistry workflows and molecular simulations through a high-level cloud-based Python API.
Optimizes ML data workflows using Polars, Arrow, and ClickHouse for high-performance, memory-efficient pipeline development.
Implements validation patterns to catch machine learning errors early and prevent wasted GPU resources during long-running experiments.
Deploys and integrates privacy-focused local large language models with Ollama, LocalAI, and Home Assistant.
Enables advanced visual analysis, OCR-style text extraction, and multi-page document processing within Claude.
Implements document-based citations and Retrieval-Augmented Generation (RAG) patterns to ensure grounded, verifiable AI responses.
Manages a local research paper database to extract equations, summaries, and context for grounding AI-generated code in scientific literature.
Provides expert patterns for rigorous statistical modeling, econometrics, and hypothesis testing within Claude Code.
Detects and prevents data leakage in machine learning feature sets to ensure model performance generalizes to production.
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