data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Generates professional Excel pivot tables and visualizations from raw data using simple natural language commands.
Generates standardized, regulatory-compliant clinical documentation and medical reports following global healthcare guidelines.
Automates complex Google Vertex AI multimodal operations for advanced video processing, high-fidelity image generation, and end-to-end marketing campaign orchestration.
Automates the integration and configuration of experiment tracking tools like MLflow and Weights & Biases for machine learning projects.
Automates financial budget-vs-actual variance analysis with professional reporting, automated commentary, and executive summaries.
Automates the fine-tuning and adaptation of pre-trained machine learning models for specific tasks and new datasets.
Facilitates collaborative research ideation to generate novel hypotheses, identify research gaps, and develop innovative scientific methodologies.
Infers large-scale gene regulatory networks from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.
Productionizes machine learning models and builds scalable MLOps systems with world-class engineering standards.
Integrates Claude with the Benchling R&D platform to automate lab data management, registry entities, and inventory workflows via Python SDK and REST API.
Accesses and retrieves nucleotide sequences, raw reads, and genomic metadata from the European Nucleotide Archive (ENA).
Predicts high-accuracy 3D protein-ligand binding poses using state-of-the-art diffusion-based deep learning models.
Builds and executes automated ETL pipelines for cleaning, validating, and transforming raw datasets into model-ready formats.
Generates publication-ready clinical decision support documents, biomarker-stratified cohort analyses, and evidence-based treatment guidelines.
Provides a comprehensive toolkit for time series machine learning including classification, forecasting, and anomaly detection using scikit-learn compatible APIs.
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.
Transforms raw datasets into insightful charts, plots, and graphs using intelligent data analysis and automated library selection.
Enables efficient searching, metadata retrieval, and PDF downloads from the bioRxiv preprint server for life sciences research.
Provides interpretability and transparency for machine learning models by explaining predictions and identifying key feature importance.
Analyzes, manipulates, and visualizes phylogenetic and hierarchical trees for genomic research and bioinformatics.
Identifies outliers and unusual patterns in datasets using advanced machine learning algorithms.
Predicts future values and identifies patterns in historical time-dependent data using advanced statistical models.
Conducts real-time academic research and technical documentation searches using Perplexity's Sonar models with automated citations.
Executes autonomous multi-step biomedical research tasks across genomics, drug discovery, and clinical analysis.
Optimizes deep learning models by refining architectures, tuning hyperparameters, and improving training efficiency.
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.
Develops, deploys, and manages serverless bioinformatics pipelines using the Latch SDK and cloud infrastructure.
Detects system hardware capabilities to provide strategic recommendations for computationally intensive scientific tasks.
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