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A demonstration of the explainerdashboard package that that displays model quality, permutation importances, SHAP values and interactions, and individual trees for sklearn RandomForestClassifiers, etc
This module extends the kernel SHAP method (as introduced by Lundberg and Lee (2017)) which is local in nature, to a method that computes global SHAP values.
Glass-box autonomous data science in Python. Profiles data, builds leakage-safe pipelines, recommends and tunes models, and logs every decision behind the result.
Determinant is not an “AI agent framework.” It is a runtime for executing structured programs that may include agents, where every run is reproducible, inspectable, and explainable.
Explainable document transparency analyzer -- scores how well text backs its claims with sources and flags overclaiming, vague attribution, and loaded language. Pure-Python CLI, no API key, with a measured precision/recall eval.
Detección de duplicados y búsqueda por similitud en datos tabulares. Las heurísticas de tu dominio son configuración, no código, y cada veredicto viene explicado. Aplicación de escritorio, línea de comandos y API en Python.
Offline job search workflow: filter, deduplicate, rank and track job listings from any source. Explainable rejection reasons, quota simulation, standard library only, zero network calls.