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 advanced prompt engineering techniques to maximize LLM performance, reliability, and structured output quality.
Predicts future values and identifies patterns in historical time-dependent data using advanced statistical models.
Performs exact symbolic mathematics in Python, including calculus, algebra, and complex equation solving.
Provides a comprehensive toolkit for time series machine learning including classification, forecasting, and anomaly detection using scikit-learn compatible APIs.
Automates regression modeling and data analysis to identify relationships between variables and predict future trends.
Infers large-scale gene regulatory networks from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.
Integrates Claude with the Benchling R&D platform to automate lab data management, registry entities, and inventory workflows via Python SDK and REST API.
Enables efficient searching, metadata retrieval, and PDF downloads from the bioRxiv preprint server for life sciences research.
Analyzes cryptocurrency market sentiment, social trends, and on-chain data to generate actionable trading insights and risk assessments.
Builds and executes automated ETL pipelines for cleaning, validating, and transforming raw datasets into model-ready formats.
Automates the fine-tuning and adaptation of pre-trained machine learning models for specific tasks and new datasets.
Generates publication-ready clinical decision support documents, biomarker-stratified cohort analyses, and evidence-based treatment guidelines.
Detects system hardware capabilities to provide strategic recommendations for computationally intensive scientific tasks.
Provides interpretability and transparency for machine learning models by explaining predictions and identifying key feature importance.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank for research, drug discovery, and interaction analysis.
Orchestrates complex multi-agent systems using the AI SDK v5 to facilitate intelligent task routing and seamless agent handoffs.
Conducts real-time academic research and technical documentation searches using Perplexity's Sonar models with automated citations.
Identifies outliers and unusual patterns in datasets using advanced machine learning algorithms.
Optimizes deep learning models by refining architectures, tuning hyperparameters, and improving training efficiency.
Develops, deploys, and manages serverless bioinformatics pipelines using the Latch SDK and cloud infrastructure.
Transforms raw datasets into insightful charts, plots, and graphs using intelligent data analysis and automated library selection.
Accesses and retrieves nucleotide sequences, raw reads, and genomic metadata from the European Nucleotide Archive (ENA).
Automates the integration and configuration of experiment tracking tools like MLflow and Weights & Biases for machine learning projects.
Provides rapid access to 20+ genomic databases and bioinformatics tools for gene searching, sequence alignment, and protein structure prediction.
Automates the creation of professional-grade Leveraged Buyout (LBO) models in Excel for private equity and investment analysis.
Automates the fine-tuning and adaptation of pre-trained machine learning models for new tasks and datasets.
Create publication-quality statistical graphics and complex data visualizations using the Seaborn Python library.
Develops and trains sophisticated Graph Neural Networks (GNNs) for irregular data structures using the PyTorch Geometric library.
Executes autonomous multi-step biomedical research tasks across genomics, drug discovery, and clinical analysis.
Constructs and configures custom neural network architectures including CNNs, RNNs, and Transformers directly within the Claude Code environment.
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