data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Orchestrates complex multi-agent systems using AI SDK v5 to facilitate intelligent routing, agent handoffs, and coordinated AI workflows.
Generates high-quality charts, plots, and graphs from raw data to reveal patterns and insights through intelligent automated visualization.
Optimizes LLM prompts to reduce token usage, lower costs, and enhance response performance through intelligent rewriting.
Analyzes and processes images using computer vision techniques like object detection, classification, and segmentation.
Provides interpretability and transparency for machine learning models by generating explanations for predictions and identifying feature importance.
Automates regression modeling and predictive data analysis to identify trends and relationships between variables.
Removes batch effects from merged bulk RNA-seq or microarray cohorts using the ComBat algorithm to ensure data consistency for downstream analysis.
Generates professional PDF reports with formatted text, tables, and embedded visualizations using the reportlab Python library.
Optimizes deep learning models by refining architectures, tuning hyperparameters, and implementing advanced training strategies to improve accuracy and efficiency.
Executes and visualizes machine learning clustering algorithms to identify groups and structures within provided datasets.
Orchestrates complex multi-agent systems using AI SDK v5 to facilitate intelligent routing, agent handoffs, and coordinated workflows across multiple AI providers.
Evaluates and improves the ethical integrity and fairness of AI models and datasets through automated bias detection and mitigation strategies.
Generates informative and visually appealing charts, plots, and graphs through intelligent data analysis and automated selection of optimal visualization types.
Analyzes text data to identify emotional tone and classify sentiment as positive, negative, or neutral.
Identifies outliers and unusual patterns in datasets using machine learning algorithms to uncover potential errors, fraud, or security threats.
Analyzes text data to identify emotional tone and classify sentiment as positive, negative, or neutral.
Builds and deploys production-ready generative AI agents leveraging Google Cloud's Vertex AI platform and Gemini models.
Refines and streamlines LLM prompts to minimize token consumption, reduce operational costs, and maximize response quality.
Builds and deploys production-grade Firebase Genkit applications including RAG systems, multi-step workflows, and AI monitoring across Node.js, Python, and Go.
Designs and implements personalized recommendation engines using collaborative filtering, content-based filtering, and hybrid modeling techniques.
Performs regression analysis and predictive modeling to identify relationships between variables and forecast future data trends.
Automates the transition of machine learning models into production environments through optimized deployment workflows and API serving.
Automates the division of datasets into training, validation, and testing subsets for machine learning workflows.
Partitions datasets into training, validation, and testing sets to prepare data for machine learning workflows.
Optimizes deep learning models to improve accuracy, reduce training duration, and minimize resource consumption through advanced algorithms and architectural analysis.
Optimizes machine learning model configurations using advanced search strategies to maximize predictive performance and efficiency.
Performs advanced natural language processing to extract sentiment, identify keywords, and model topics from textual data.
Evaluates AI models and datasets for bias, fairness, and ethical compliance using industry-standard metrics and frameworks.
Automates the end-to-end machine learning lifecycle including data analysis, model selection, training, evaluation, and artifact generation.
Engineers production-ready Agent Development Kit (ADK) applications with robust architecture, comprehensive testing, and automated deployment pipelines.
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