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Explaining Machine Learning Models

explaining-machine-learning-models

jeremylongshore/claude-code-plugins-plus-skills

Provides interpretable explanations for ML predictions using SHAP, LIME, and other techniques, helping debug model behavior, highlight feature importance, and communicate fairness insights to stakeholders.

Shap Model Interpretation

K-Dense-AI/claude-scientific-skills

Explain machine learning predictions with SHAP values, generate global and local plots (beeswarm, waterfall, force), compare models, debug bias, and ship explainable AI in production.

AI-Shaped Readiness Advisor

ai-shaped-readiness-advisor

deanpeters/Product-Manager-Skills

Interactive assessment that gauges whether your product work is AI-first or AI-shaped, measures readiness across five essential PM competencies for 2026, highlights gaps, and recommends which AI capability to build next.

LeCun Philosophy Module

yann-lecun-filosofia

sickn33/antigravity-awesome-skills

Emulates Yann LeCun’s open-source philosophy and pedagogical persona to help explore LLaMA history, corporate incentives, Socratic teaching, and how open science shapes AI research and accountability.

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