Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Automates end-to-end empirical data analysis workflows using Stata and R for publication-ready research output.
Audits R projects against UK Government Reproducible Analytical Pipelines (RAP) maturity standards to ensure code quality and transparency.
Performs production-ready financial analysis including DCF valuations, ratio calculations, and budget variance monitoring.
Performs diffusion-based molecular docking to predict high-accuracy 3D binding poses between proteins and ligands for drug discovery.
Streamlines the development of AI-powered applications using Vercel's universal AI SDK for TypeScript and JavaScript.
Implements adaptive learning systems for AI agents to recognize patterns, optimize strategies, and improve autonomously through experience.
Calculates advanced economic statistics and estimates using specialized R methodologies for weighted and bunched data.
Provides comprehensive technical specifications and implementation patterns for Google's Veo 3.1 video generation model.
Implements rigorous evaluation strategies for AI applications using automated metrics, human feedback, and LLM-as-judge patterns.
Transcribes MP3, WAV, and M4A audio files into text using hardware-accelerated MLX Whisper on Apple Silicon.
Detects and analyzes system hardware to provide strategic architectural recommendations for computationally intensive scientific tasks.
Analyzes, summarizes, and documents robot learning experiment runs across local and cluster environments.
Orchestrates dynamic AI agent swarms by automatically switching between hierarchical, mesh, and ring topologies based on real-time performance metrics.
Manages local GGUF model inference and API serving through llama.cpp within worker terminals.
Standardizes backend-agnostic tensor math for BayesFlow extensions using the Keras 3 functional API.
Builds professional-grade discounted cash flow (DCF) valuation models in Excel with automated financial projections and sensitivity analysis.
Deploys and trains sophisticated neural networks across distributed E2B sandboxes with support for custom architectures and federated learning.
Creates sophisticated, interactive, and publication-quality data visualizations using the D3.js library.
Guides developers through selecting, implementing, and optimizing vector search solutions for AI applications and RAG pipelines.
Optimizes AI agent performance through SONA-powered self-learning, LoRA fine-tuning, and memory-safe pattern discovery.
Simplifies the creation, configuration, and debugging of Kodexa model and skill modules using standardized YAML and Python templates.
Conducts multi-perspective cryptocurrency market analysis using a coordinated swarm of specialized AI agents.
Streamlines the creation, modification, and debugging of BayesFlow 2.x simulators for simulation-based inference.
Analyzes complex networks and calculates PageRank scores using sublinear algorithms to optimize graph structures and influence mapping.
Automates the end-to-end machine learning lifecycle from data preprocessing and feature engineering to model training and deployment.
Implements persistent, high-performance memory and learning patterns for AI agents using AgentDB vector storage.
Implements high-performance adaptive learning and memory distillation for Claude using AgentDB's ultra-fast vector database.
Optimizes AI agent action spaces and tool definitions to maximize completion rates and operational reliability.
Implements ultra-fast semantic vector search and intelligent document retrieval using high-performance AgentDB indexing.
Implements high-performance persistent memory and reinforcement learning patterns for AI agents and intelligent assistants.
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