Discover Agent Skills for data science & ml. Browse 61skills for Claude, ChatGPT & Codex.
Implements production-grade sorting and searching algorithms with comprehensive complexity analysis and unit testing templates.
Implements a triadic framework balancing category theory, cybernetic agency, and phenomenological observation for complex system modeling.
Replaces temporal succession with deterministic seed-chaining to enable verifiable, frame-invariant state transitions.
Builds and validates high-fidelity psychological models to predict behaviors and generate authentic cognitive responses matching a subject's unique patterns.
Implements a rigorous 6-phase framework for conducting and analyzing qualitative research with mandatory bias prevention and reproducible methodology.
Generates professional data-driven presentations and whitepapers using Marp and Pandoc with full citation support and reproducibility.
Guides rigorous, intellectually honest interpretation of data query results to ensure objective and actionable conclusions.
Generates professional terminal-based and image-based data visualizations to enhance analytical insights and documentation.
Implements high-performance semantic vector search and intelligent document retrieval for RAG systems and context-aware applications.
Implements high-performance persistent memory and pattern learning for stateful AI agents using AgentDB.
Optimizes document retrieval and semantic search workflows using RAG best practices, vector databases, and advanced chunking strategies.
Deploys and manages production-grade machine learning models on Databricks with support for A/B testing and auto-scaling.
Build and manage declarative, self-healing data pipelines with built-in quality enforcement and automated lineage tracking.
Implements automated model monitoring, drift detection, and performance tracking for production machine learning systems on Databricks.
Optimizes machine learning workflows on Databricks by implementing structured MLflow experiment tracking and model governance patterns.
Streamlines the creation, management, and serving of scalable feature stores within the Databricks MLOps ecosystem.
Standardizes robotics datasets and deploys edge-optimized vision-language-action models for embodied AI applications.
Converts URDF robot descriptions into MJCF format for high-performance MuJoCo and MJX physics simulations.
Builds and simulates a cost-efficient, wobbling robot that composes nonstandard musical scales through duck-like vocalizations.
Trains humanoid locomotion and manipulation policies using JAX-accelerated MuJoCo simulations and advanced RL algorithms.
Synthesizes Patrick Kenny's active inference framework with K-Scale's JAX/MuJoCo robotics stack for advanced predictive coding in robot locomotion.
Provides a unified framework for humanoid robot development, reinforcement learning training, and sim-to-real deployment.
Provides hardware specifications, MuJoCo MJCF models, and deployment workflows for the K-Scale flagship humanoid robot platform.
Deploys trained Reinforcement Learning (RL) policies to real robots using high-performance Rust and ONNX Runtime.
Bridges the gap between robotic simulations and real-world deployment using maximum entropy reinforcement learning and information-theoretic alignment.
Composes complex 3D environments and terrains for robotic simulation and reinforcement learning training.
Implements a compositional AI framework based on category theory and GF(3) triadic balance for deterministic, self-modifying agent architectures.
Facilitates the development, simulation, and control of 3D-printed humanoid robots for reinforcement learning research.
Performs ultra-fast portfolio backtesting and trading strategy analysis using the Polars library.
Simplifies the creation of LLM-powered applications and autonomous agents using standardized LangChain implementation patterns.
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