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。
Optimizes Large Language Model prompts to minimize token usage, reduce operational costs, and enhance response quality.
Provides a persistent cognitive architecture for AI agents to maintain long-term memory, context, and identity across multiple sessions.
Connects Claude to the NIH Metabolomics Workbench for comprehensive access to metabolite data, study metadata, and mass spectrometry search capabilities.
Organizes and scales PyTorch code into modular, high-performance deep learning workflows with minimal boilerplate.
Manages and tracks machine learning model versions, performance metrics, and lineage directly within Claude Code.
Performs advanced materials analysis, crystal structure manipulation, and Materials Project database integration for computational scientists.
Applies medicinal chemistry rules and structural filters to prioritize and triage molecular libraries for drug discovery.
Performs exact symbolic mathematics in Python, including calculus, algebra, and complex equation solving.
Automates image analysis, object detection, and classification workflows directly within Claude Code.
Accesses the ZINC repository of over 230 million purchasable compounds to streamline virtual screening and drug discovery workflows.
Generates standardized, regulatory-compliant clinical documentation and medical reports following global healthcare guidelines.
Generates professional Excel pivot tables and visualizations from raw data using simple natural language commands.
Automates regression modeling and data analysis to identify relationships between variables and predict future trends.
Predicts future values and identifies patterns in historical time-dependent data using advanced statistical models.
Provides a comprehensive toolkit for time series machine learning including classification, forecasting, and anomaly detection using scikit-learn compatible APIs.
Productionizes machine learning models and builds scalable MLOps systems with world-class engineering standards.
Automates complex Google Vertex AI multimodal operations for advanced video processing, high-fidelity image generation, and end-to-end marketing campaign orchestration.
Orchestrates multi-agent deliberations and structured critiques across multiple LLMs to provide optimized architectural and coding recommendations.
Automates the integration and configuration of experiment tracking tools like MLflow and Weights & Biases for machine learning projects.
Automates the fine-tuning and adaptation of pre-trained machine learning models for specific tasks and new datasets.
Integrates Claude with the Benchling R&D platform to automate lab data management, registry entities, and inventory workflows via Python SDK and REST API.
Infers large-scale gene regulatory networks from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.
Enables efficient searching, metadata retrieval, and PDF downloads from the bioRxiv preprint server for life sciences research.
Generates publication-ready clinical decision support documents, biomarker-stratified cohort analyses, and evidence-based treatment guidelines.
Builds and executes automated ETL pipelines for cleaning, validating, and transforming raw datasets into model-ready formats.
Transforms raw datasets into insightful charts, plots, and graphs using intelligent data analysis and automated library selection.
Orchestrates complex multi-agent systems using the AI SDK v5 to facilitate intelligent task routing and seamless agent handoffs.
Accesses and analyzes comprehensive pharmaceutical data from DrugBank for research, drug discovery, and interaction analysis.
Develops, deploys, and manages serverless bioinformatics pipelines using the Latch SDK and cloud infrastructure.
Optimizes deep learning models by refining architectures, tuning hyperparameters, and improving training efficiency.
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