data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Optimizes deep learning model performance by refining architectures, tuning hyperparameters, and implementing efficient training strategies.
Automates the configuration and initialization of machine learning experiment tracking tools like MLflow and Weights & Biases.
Conducts systematic computational text analysis for sociology research using R or Python with a focus on validation and reproducibility.
Automates the partitioning of datasets into training, validation, and testing sets to streamline machine learning workflows.
Streamlines data preparation for machine learning by building automated pipelines for cleaning, validation, and transformation.
Enables Claude to analyze images, detect objects, and perform visual classification tasks directly within your development workflow.
Automates the partitioning of datasets into optimized training, validation, and testing subsets for machine learning workflows.
Simplifies running, converting, and serving Large Language Models on Apple Silicon using the MLX framework.
Develops personalized recommendation engines using collaborative filtering, content-based analysis, and hybrid modeling techniques.
Automates the creation, training, and evaluation of machine learning models through comprehensive end-to-end pipelines.
Automates the end-to-end creation, training, and evaluation of machine learning pipelines to accelerate model development workflows.
Processes and analyzes images using advanced computer vision techniques to identify objects, classify scenes, and segment visual data.
Conducts publication-ready quantitative sociological research using phased R workflows and rigorous econometric methods.
Evaluates AI models and datasets for ethical risks, bias, and fairness to ensure responsible machine learning development.
Validates the ethical implications and fairness of AI/ML models and datasets to ensure responsible development.
Refines and condenses AI prompts to minimize token consumption while maximizing output quality and performance.
Retrieves relevant past episodes and patterns from episodic memory to inform AI decision-making and task execution.
Orchestrates complex multi-agent workflows using AI SDK v5 to manage handoffs, intelligent routing, and cross-provider coordination.
Accesses and integrates data from over 40 bioinformatics web services and databases using a unified Python API.
Performs differential gene expression analysis on bulk RNA-seq data using the Python implementation of DESeq2.
Provides comprehensive Python tools for astronomical data analysis, including celestial coordinates, physical units, and FITS file manipulation.
Identifies outliers and unusual patterns in datasets using machine learning algorithms to detect fraud, errors, or security threats.
Integrates Google Gemini's advanced coding models into Claude Code for high-context refactoring, deep analysis, and automated file editing.
Streamlines the development of distributed AI agents using the Dapr framework by validating configurations and implementing best-practice patterns.
Automates the end-to-end machine learning lifecycle from data analysis and model selection to training and performance evaluation.
Identifies outliers and unusual patterns in datasets using machine learning to uncover fraud, security threats, or data irregularities.
Performs advanced regression analysis and predictive modeling to identify variable relationships and forecast data trends using automated statistical tools.
Optimizes LLM prompts for high-accuracy text classification through a systematic, evaluation-driven workflow.
Transforms vague natural language inputs into precision-engineered prompts for Claude, ChatGPT, Gemini, and other large language models.
Builds interactive, publication-quality data visualizations using the D3.js library for any JavaScript environment.
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