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。
Simplifies molecular cheminformatics and drug discovery workflows using a Pythonic interface for RDKit.
Executes autonomous multi-step biomedical research tasks across genomics, drug discovery, and clinical analysis using integrated databases and code execution.
Applies unsupervised machine learning models to genomic interval data for embedding, clustering, and bioinformatics analysis.
Verifies that machine learning models correctly respect intended symmetries through systematic numerical tests and debugging guidance.
Stress-tests predictions by assuming failure and working backward to identify hidden risks and blind spots.
Accesses the RCSB Protein Data Bank to search, retrieve, and analyze 3D structural data for biological macromolecules.
Structures clinical research and evaluates health evidence using established evidence-based medicine frameworks like PICOT and GRADE.
Systematically investigates causal relationships to identify fundamental root causes and distinguish them from symptoms or correlations.
Provides structured frameworks and systematic workflows for Test-Driven Development (TDD), data exploration, and statistical modeling.
Generates publication-quality statistical graphics and exploratory data visualizations using the Seaborn Python library.
Implements systematic Bayesian probability updates to improve forecasting and decision-making under uncertainty.
Explains machine learning model predictions and feature importance using SHapley Additive exPlanations (SHAP) across various model architectures.
Establishes objective statistical baselines for predictions and projects by anchoring them in historical reality and the 'Outside View.'
Builds custom, interactive data-driven visualizations using D3.js for complex layouts, maps, and bespoke charting requirements.
Maps identified symmetries to mathematical groups to formalize requirements for equivariant and invariant neural network architectures.
Quantifies uncertain business choices and crafts persuasive, data-backed narratives to secure stakeholder buy-in.
Matches data questions to optimal chart types and generates narrated reports that turn raw metrics into actionable business insights.
Designs neural network architectures that preserve symmetry groups to improve model efficiency and robustness.
Parses and creates Flow Cytometry Standard (FCS) files for seamless integration with Python data science workflows.
Simplifies complex time series machine learning tasks including forecasting, classification, and anomaly detection using a scikit-learn compatible toolkit.
Detects and mitigates cognitive biases to improve decision-making, forecasting accuracy, and intellectual honesty.
Enhances Glide apps with AI-powered columns for text generation, OCR, transcription, and automated data processing.
Optimizes training epochs for machine learning models using Walk-Forward Efficiency and efficient frontier analysis.
Evaluates financial models using state-of-the-art metrics specifically designed for range bar (price-based sampling) data.
Interacts with the Replicate AI platform to run models, manage deployments, and perform fine-tuning directly from the command line.
Automates professional spreadsheet creation, complex financial modeling, and data analysis with formula-driven accuracy.
Leverages a multi-model ensemble to provide diverse, parallel insights from GPT, Gemini, and Claude for complex problem-solving.
Analyzes and evaluates LLM prompts using a structured 10-Layer Architecture to improve clarity, precision, and output performance.
Calculates probability-weighted outcomes to facilitate rational decision-making under uncertainty for investments, product development, and strategic initiatives.
Generates evidence-based, testable scientific hypotheses and structured experimental designs to accelerate research and discovery.
Scroll for more results...