Slides and notebooks for serving BERT models in production with PyTorch and TorchServe.
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Updated
Aug 21, 2026 - Jupyter Notebook
Slides and notebooks for serving BERT models in production with PyTorch and TorchServe.
Algorithmia Github Action capable of running Jupyter notebooks to create the ML model, uploading the model and updating the algorithm at Algorithmia
Demonstrating how to build an XGBoost model and deploy it to Algorithmia, from a Jupyter notebook
Hands-on MLflow example repository with notebooks and scripts for tracking, experiment management, model registry, serving, projects, pipelines, evaluation, and hyperparameter tuning.
Production-style ML inference service taking a trained model from notebook to deployed API with monitoring, containerisation, CI/CD, Kubernetes, and cloud infrastructure
Three ML projects taken past the notebook: SMS spam classification, car price regression and housing regression - each served over HTTP and evaluated in the way that would expose it if it were wrong.
To associate your repository with the model-serving topic, visit your repo's landing page and select "manage topics."