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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.

SLIME RL Training

slime-rl-training

Orchestra-Research/AI-Research-SKILLs

Guides post-training of GLM-class LLMs with Megatron-LM and SGLang, focusing on GRPO rollout generation, custom data buffers, and tight RL scaling workflows for research and production use.

Linux Memory Forensics Workflow

analyzing-memory-forensics-with-lime-and-volatility

mukul975/Anthropic-Cybersecurity-Skills

Guides acquiring Linux memory with LiME and analyzing it through Volatility 3 to extract processes, bash history, network connections, kernel modules, and injected code during incident response and threat hunting.

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