Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Accelerates data manipulation and ETL pipelines with the high-performance Polars DataFrame library.
Explains machine learning model predictions and feature importance using SHAP values and comprehensive visualizations.
Trains and deploys complex neural network architectures within distributed E2B sandbox environments for scalable machine learning workflows.
Builds, evaluates, and deploys production-ready machine learning models using the industry-standard scikit-learn library.
Implements and trains advanced reinforcement learning algorithms to create autonomous agents that evolve through experience.
Extracts and analyzes narrative arcs, causality, and token novelty from complex text and codebases.
Implements the DRIVER framework for structured, collaborative financial tool development and quantitative analysis.
Develops and trains Graph Neural Networks (GNNs) for node classification, link prediction, and geometric deep learning tasks.
Optimizes LangGraph application performance by iteratively refining prompts and node-level processing logic based on quantitative evaluation criteria.
Generates interactive, publication-quality Python charts and dashboards for data exploration and presentation.
Implements high-performance, Rust-powered tokenization for training and deploying custom NLP models with speed and precision.
Initializes a standardized project structure for financial underwriting and quant development using the DRIVER methodology.
Orchestrates multi-agent AI systems for parallel task execution and intelligent workflow coordination using dynamic topologies.
Performs automated exploratory data analysis and generates comprehensive reports for over 200 scientific file formats.
Implements high-performance adaptive learning and memory distillation for AI agents using the ultra-fast AgentDB vector engine.
Train, deploy, and manage distributed neural networks within E2B sandboxes using the Flow Nexus ecosystem.
Provides comprehensive financial frameworks for modeling, valuation, corporate finance decisions, and advanced statement analysis.
Implements advanced prompt engineering techniques to maximize LLM performance, reliability, and reasoning capabilities in production environments.
Builds high-performance Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search to ground LLMs in external data.
Implements comprehensive evaluation frameworks to measure LLM application quality using automated metrics, human feedback, and comparative benchmarks.
Provides a comprehensive framework and guidance for building professional finance and quantitative analysis tools with AI assistance.
Optimizes AI agent behavior through specialized prompt engineering patterns and best practices for complex, autonomous workflows.
Converts chemical structures into numerical representations for molecular machine learning and drug discovery workflows.
Builds, optimizes, and executes quantum circuits and algorithms on real hardware and high-performance simulators.
Analyzes and models strange attractors with sensitive dependence on initial conditions within complex dynamical systems.
Implements standardized Agent-to-Agent (A2A) protocol executors with production-ready patterns for task management and agent coordination.
Converts audio files into high-quality timestamped transcriptions using NVIDIA's Parakeet model optimized for Apple Silicon.
Orchestrates complex multi-agent systems on AWS using the Bedrock AgentCore Agent-to-Agent (A2A) protocol.
Analyzes global nickel supply structures and quantifies market concentration risks through policy simulation and data-driven metrics.
Analyzes bond market volatility as a leading indicator for equity fear and credit spreads using cross-correlation and shock-event testing.
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