Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Generates professional, publication-ready clinical decision support documents and biomarker-stratified cohort analyses for pharmaceutical and clinical research.
Analyzes the emotional tone of text data to classify sentiment as positive, negative, or neutral for customer feedback and social media monitoring.
Manages and tracks AI/ML model versions, performance metrics, and lineage directly within the Claude Code environment.
Automates the transition of machine learning models into production-ready environments and high-performance APIs.
Configures authentication credentials for external AI services including OpenAI GPT and Google Gemini.
Splits PDF documents into optimized segments using token-based text extraction or layout-preserving page division.
Monitors and analyzes trading strategy performance to identify statistical alpha decay and regime changes.
Guides artists and developers through the end-to-end process of training custom AI art models with a focus on dataset quality and resource optimization.
Transforms raw datasets into informative and visually compelling charts, plots, and graphs using intelligent automated selection.
Empowers Claude to perform sophisticated data analysis, transformation, and reporting using advanced Microsoft Excel techniques and Power Query.
Generates professional data visualizations, charts, and graphs from raw datasets to uncover patterns and insights automatically.
Fixes prediction failures and optimizes data fetching logic for live algorithmic trading systems.
Builds sophisticated Retrieval-Augmented Generation (RAG) systems to ground AI responses in external knowledge bases and private documentation.
Streamlines R data visualization workflows with expert guidance on ggplot2 4.0 features and grammar of graphics implementation.
Conducts rigorous A/B testing and cost-benefit analysis to validate the impact of Claude-driven agents on reinforcement learning model performance.
Executes machine learning clustering algorithms to identify patterns, groups, and anomalies within complex datasets.
Executes sophisticated clustering algorithms on datasets to uncover hidden patterns, identify data groupings, and detect anomalies.
Standardizes the creation of Google Colab notebooks for machine learning and trading experiments using a high-performance template.
Provides specialized guidance and code patterns for interpreting machine learning models using scikit-learn, SHAP, and advanced diagnostic tools.
Automates the conversion of high-resolution microscopy images into web-optimized DZI tiles and .tmap project files for TissUUmaps visualization.
Manages large-scale numerical datasets using the HDF5 binary format and NumPy-compatible interfaces for high-performance data science.
Visualizes code changes, algorithm results, and data states by displaying multiple outputs in parallel columns.
Automates systematic literature reviews by searching academic databases, synthesizing findings, and generating publication-ready documents with verified citations.
Conducts real-time academic research and literature reviews using Perplexity’s advanced Sonar models with automated citation generation.
Builds production-grade AI features using robust LLM integration patterns, prompt versioning, and cost-optimized RAG architectures.
Implements production-grade LLM integration patterns, scalable prompt engineering, and cost-optimized AI architectures.
Optimizes vector database performance by fine-tuning HNSW parameters, quantization strategies, and memory usage for high-scale search applications.
Automates professional spreadsheet creation, data analysis, and financial modeling with industry-standard formatting and formula integrity.
Builds reliable AI agents using robust patterns like ReAct and Plan-Execute while prioritizing guardrails and self-correction.
Builds production-grade AI applications using advanced RAG patterns, prompt engineering, and LLM orchestration frameworks.
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