Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Identifies and prioritizes research gaps from systematic literature reviews to justify new studies and grant proposals.
Implements rigorous blinding protocols to minimize bias and ensure objectivity in experimental studies and clinical trials.
Implements standardized patterns for summing tax and benefit variables across entities using the adds attribute and add() function.
Generates structured evidence synthesis matrices to organize and compare research data for systematic reviews.
Implements high-performance adaptive learning and memory distillation for AI agents using the AgentDB vector backend.
Calculates and interprets standardized effect sizes to quantify the magnitude of research findings beyond simple p-values.
Implements adaptive learning and meta-cognitive capabilities for AI agents to optimize strategies based on historical experience.
Implements L0 regularization and intelligent sampling techniques to optimize neural network sparsification and survey data calibration.
Implements comprehensive evaluation frameworks for LLM applications using automated metrics, LLM-as-Judge patterns, and human feedback loops.
Simplifies the creation of interactive, publication-quality visualizations using hvPlot and HoloViews within the HoloViz ecosystem.
Applies perceptually uniform colormaps and accessible visual styling to data visualizations using Colorcet and the HoloViz ecosystem.
Implements type-safe, declarative configuration and reactive logic using the Param library for Python applications.
Converts literary works into high-quality supervised fine-tuning (SFT) datasets for training distinctive author-voice and style-transfer models.
Optimizes vector index performance for production-grade latency, recall, and memory efficiency in AI applications.
Implements advanced prompt engineering techniques like few-shot learning and chain-of-thought to maximize LLM performance and reliability.
Implements robust evaluation frameworks for AI applications using automated metrics, human feedback, and LLM-as-judge patterns.
Architects and implements robust LLM-powered projects from initial ideation through deployment using agentic methodologies.
Designs and implements sophisticated LLM applications using the LangChain framework for agents, memory management, and complex task workflows.
Implements a cognitive immune framework using active inference and information geometry for robust system self-maintenance.
Implements production-ready architectural patterns and scalable designs for enterprise LangChain applications.
Standardizes machine learning experiment management using Hydra and OmegaConf configuration patterns.
Automates the transfer of HuggingFace models to RunPod Network Volumes via Google Colab to minimize GPU billing costs.
Builds, evaluates, and deploys code-first AI agents and multi-agent systems using Google's Agent Development Kit.
Extracts and analyzes metadata from NetCDF and CDL files into structured CSV format for documentation and data analysis.
Analyzes market trends and technical indicators to provide actionable trading insights and detailed risk assessments.
Designs resilient contingency module architectures to manage failure scenarios within AI governance frameworks.
Executes complex numerical calculations, linear algebra operations, and scientific computing tasks using the high-performance Julia language.
Builds and executes LLM-powered data processing pipelines for unstructured document analysis using DocETL and Claude Haiku.
Retrieves global atmospheric, land, and ocean climate reanalysis data from the Copernicus Climate Data Store using the CDS API.
Optimizes token usage and reduces operational costs when delegating tasks to the Gemini CLI.
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