Results for “explainable-ai”

Generates high-fidelity images using reasoning-driven prompts and structured creative briefs via muapi.ai.

Interpretabilidade e explicabilidade de modelos usando SHAP (SHapley Additive exPlanations). Use essa skill ao explicar predições de modelos de machine learning, computar importância de features, gerar plots SHAP (waterfall, beeswarm, bar, scatter, force, heatmap), depurar modelos, analisar vieses ou justiça de modelos, comparar modelos ou implementar IA explicável. Funciona com modelos baseados em árvores (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), modelos lineares e qualquer modelo black-box.

Create publication-quality scientific diagrams using AI generation with smart iterative refinement and quality review.

Compose a provider-neutral AI team by tiering accessible models on cost-efficiency, capability, latency, and governance, then mapping the 8 processkit role archetypes onto catalog Roles + RoleSlots inside a chartering Scope. Use when bootstrapping a new project team, rotating after a provider change, or quarterly rebalancing. Triggers: "create my AI team", "compose a team", "rebalance the team", "review the team".

A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution.