Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Implements a multi-layered persistent memory architecture that enables AI agents to learn from experience and retain knowledge across sessions.
Implements production-grade LLM-as-a-Judge techniques for evaluating AI outputs through rigorous scoring, pairwise comparisons, and bias mitigation.
Integrates Alpha Vantage APIs to fetch real-time and historical market data, technical indicators, and financial fundamentals.
Streamlines the development of Python workflows using Awkward Array for jagged, nested, and record-based data structures.
Implement efficient vector-based similarity search, semantic retrieval, and RAG patterns across major vector databases.
Implements robust Bayesian meta-analysis models using Stan and JAGS to synthesize data across multiple studies with advanced statistical precision.
Proposes structured, data-driven experiment plans by analyzing historical training reports, logs, and research goals.
Optimizes long-running AI agent sessions by implementing structured context compression to maintain technical accuracy and memory efficiency.
Integrates Claude with the FinnHub API to retrieve real-time stock quotes, fundamental data, crypto prices, and market news.
Implements production-grade prompt engineering patterns, RAG optimization, and agentic system architectures for advanced AI products.
Empowers autonomous AI agents with real-time X (Twitter) search, web search, and sandboxed Python code execution capabilities.
Processes and analyzes billion-row tabular datasets using lazy, out-of-core DataFrame operations without exceeding available RAM.
Standardizes Python experiment layouts, stage entrypoints, and asset handling for consistent data science workflows.
Builds and manages semantic knowledge graphs to enhance autonomous coding and project understanding.
Evaluates and benchmarks different embedding models to optimize semantic search and vector retrieval performance on your specific data.
Integrates Google's Gemini 3 Pro API into Python and Node.js applications with advanced reasoning and streaming capabilities.
Builds high-performance Retrieval-Augmented Generation (RAG) systems using vector databases, semantic search, and advanced retrieval patterns.
Manages, versions, and tests Amazon Bedrock prompt templates to streamline enterprise-grade prompt engineering workflows.
Builds and manages autonomous AI agents on Amazon Bedrock using foundation models, action groups, and knowledge bases.
Develops and manages reactive Python notebooks that function as pure-code files, interactive data apps, and reproducible scripts.
Integrates Google's Gemini 3 Pro API and SDK into applications for advanced reasoning, streaming chat, and large-context processing.
Streamlines the creation, versioning, and lifecycle management of Amazon Bedrock prompt templates with variable substitution and A/B testing.
Builds and orchestrates end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment.
Implements modern AI patterns including streaming responses, tool calling, and structured outputs using the Vercel AI SDK.
Plans data science and hardware optimization experiments by analyzing historical project logs and domain-specific configurations.
Optimizes LLM performance and reliability through advanced prompt engineering techniques like few-shot learning and chain-of-thought.
Evaluates Large Language Model application performance using automated metrics, human feedback loops, and LLM-as-judge frameworks.
Orchestrates the development of complete, production-ready Claude Code agents using Anthropic's official best practices for context engineering and tool design.
Generates complex AI-driven video compositions and media pipelines using the Renku CLI.
Transcribes audio files into text using a local whisper.cpp server with GPU acceleration.
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