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1. awesome-ai-explainability awesome-ai-explainability Public

   The definitive collection of the most influential research papers on making AI systems explainable and interpretable. Carefully curated to help engineers, researchers, and practitioners build trans…

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2. torchdiag torchdiag Public

   PyTorch model health diagnostics — gradient checks, dead neuron detection, training verification. Built from an SRE perspective.

   Python

3. Math_behind_ML Math_behind_ML Public

   The math inside PyTorch's engine — how linear algebra, calculus & optimization drive torch.autograd, torch.nn, and torch.optim. GHC 2025 talk materials.

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4. opik opik Public

   Forked from comet-ml/opik

   Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

   Python

5. optuna optuna Public

   Forked from optuna/optuna

   A hyperparameter optimization framework

   Python

6. pycaret pycaret Public

   Forked from pycaret/pycaret

   An open-source, low-code machine learning library in Python

   Jupyter Notebook