A 20-episode scientific guide to AI model validation, LLM evaluation, hallucination detection, reliability, robustness, statistical uncertainty, and AI assurance. Includes Python notebooks, datasets, and reproducible experiments.
machine-learning jupyter-notebook statistical-learning model-evaluation ai-safety responsible-ai model-robustness trustworthy-ai ai-assurance generative-ai llm-evaluation rag-evaluation llm-as-a-judge model-reliability hallucination-detection-binary-logic openvals ai-model-validation
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Updated
Nov 2, 2026 - Jupyter Notebook