Awesome MLOps
Section: Model Fairness and Privacy · A comprehensive set of fairness metrics for datasets and machine learning models.
Entry
Appears in 4 awesome lists
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Section: Model Fairness and Privacy · A comprehensive set of fairness metrics for datasets and machine learning models.
Section: 10. AI Safety, Alignment & Interpretability · Comprehensive toolkit for detecting, understanding, and mitigating unwanted algorithmic bias in datasets and ML models.
Section: Explainability and Fairness · A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Section: Machine Learning Frameworks · A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
InterpretML implements the Explainable Boosting Machine (EBM), a modern, fully interpretable machine learning model based on Generalized Additive Models (GAMs). This open-source package also provides visualization tools for EBMs, other glass-box models, and black-box explanations.
MoCo, SimCLR, SimSiam, Barlow Twins, BYOL, NNCLR. vissl - Self-Supervised Learning with PyTorch: RotNet, Jigsaw, NPID, ClusterFit, PIRL, SimCLR, MoCo, DeepCluster, SwAV.
Input/output validation framework for building reliable AI applications. Detects and mitigates risks through composable validators for PII, toxicity, prompt injection, and structured output validation. Features Guardrails Hub with 50+ pre-built validators. Apache 2.0 licensed.
NVIDIA's programmable guardrails toolkit: define input, dialog, retrieval, execution, and output rails that intercept the agent loop at five distinct layers using the Colang DSL. The execution rail layer specifically governs what tools the LLM can invoke and what their inputs/outputs may contain —…
🟢 — Multi-language toolkit for policy-enforced agent tool calls and audit records, with optional identity, MCP-gateway, sandboxing, reliability, and compliance components. (Microsoft) — note: official public preview; APIs and deployment patterns may change before general availability. · updated…;…
Open-source agent engineering platform (YC W24) with session replay, cost tracking, and failure detection across 10+ frameworks including CrewAI, LangGraph, and OpenAI Agents SDK. The step-by-step execution graph and cross-session metrics make it the most practical debugging layer for multi-agent…
🟢 — Full-stack AI red-teaming platform covering OpenClaw security scan, agent scan, skills scan, MCP scan, AI-infra vulnerability scan, and LLM jailbreak evaluation. (Tencent Zhuque Lab) · updated 2026-09-10); Related: agent-audit · aguara · Cisco AI Defense – skill-scanner · Cisco AI Defense –…
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains…