https://mlops.swiss-ai-center.ch/syllabus/ https://mlops.swiss-ai-center.ch/concept/ https://mlops.swiss-ai-center.ch/philosophy/ https://mlops.swiss-ai-center.ch/tools/ https://mlops.swiss-ai-center.ch/setup/ https://mlops.swiss-ai-center.ch/cheatsheet/ https://mlops.swiss-ai-center.ch/references/ https://mlops.swiss-ai-center.ch/part-1-local-training-and-evaluation/introduction/ https://mlops.swiss-ai-center.ch/part-1-local-training-and-evaluation/chapter-11-run-a-simple-ml-experiment-with-jupyter-notebook/ https://mlops.swiss-ai-center.ch/part-1-local-training-and-evaluation/chapter-12-adapt-and-move-the-jupyter-notebook-to-python-scripts/ https://mlops.swiss-ai-center.ch/part-1-local-training-and-evaluation/chapter-13-initialize-git-and-dvc-for-local-training/ https://mlops.swiss-ai-center.ch/part-1-local-training-and-evaluation/chapter-14-reproduce-the-ml-experiment-with-dvc/ https://mlops.swiss-ai-center.ch/part-1-local-training-and-evaluation/chapter-15-track-model-evolution-with-dvc/ https://mlops.swiss-ai-center.ch/part-1-local-training-and-evaluation/conclusion/ https://mlops.swiss-ai-center.ch/part-2-move-to-the-cloud/introduction/ https://mlops.swiss-ai-center.ch/part-2-move-to-the-cloud/chapter-21-move-the-ml-experiment-code-to-the-cloud/ https://mlops.swiss-ai-center.ch/part-2-move-to-the-cloud/chapter-22-move-the-ml-experiment-data-to-the-cloud/ https://mlops.swiss-ai-center.ch/part-2-move-to-the-cloud/chapter-23-reproduce-the-ml-experiment-in-a-cicd-pipeline/ https://mlops.swiss-ai-center.ch/part-2-move-to-the-cloud/chapter-24-track-model-evolution-in-the-cicd-pipeline-with-cml/ https://mlops.swiss-ai-center.ch/part-2-move-to-the-cloud/chapter-25-work-efficiently-and-collaboratively-with-git/ https://mlops.swiss-ai-center.ch/part-2-move-to-the-cloud/conclusion/ https://mlops.swiss-ai-center.ch/part-3-serve-and-deploy/introduction/ https://mlops.swiss-ai-center.ch/part-3-serve-and-deploy/chapter-31-save-and-load-the-model-with-bentoml/ https://mlops.swiss-ai-center.ch/part-3-serve-and-deploy/chapter-32-serve-the-model-locally-with-bentoml/ https://mlops.swiss-ai-center.ch/part-3-serve-and-deploy/chapter-33-build-and-publish-the-model-with-bentoml-and-docker-locally/ https://mlops.swiss-ai-center.ch/part-3-serve-and-deploy/chapter-34-build-and-publish-the-model-with-bentoml-and-docker-with-the-cicd-pipeline/ https://mlops.swiss-ai-center.ch/part-3-serve-and-deploy/chapter-35-deploy-and-access-the-model-on-kubernetes/ https://mlops.swiss-ai-center.ch/part-3-serve-and-deploy/chapter-36-continuous-deployment-of-the-model-with-the-cicd-pipeline/ https://mlops.swiss-ai-center.ch/part-3-serve-and-deploy/chapter-37-use-a-self-hosted-runner-for-the-cicd-pipeline/ https://mlops.swiss-ai-center.ch/part-3-serve-and-deploy/chapter-38-train-the-model-on-a-kubernetes-pod/ https://mlops.swiss-ai-center.ch/part-3-serve-and-deploy/conclusion/ https://mlops.swiss-ai-center.ch/part-4-monitor-and-maintain/introduction/ https://mlops.swiss-ai-center.ch/part-4-monitor-and-maintain/chapter-41-log-predictions-and-features-locally/ https://mlops.swiss-ai-center.ch/part-4-monitor-and-maintain/chapter-42-detect-drift-locally-with-evidently-ai/ https://mlops.swiss-ai-center.ch/part-4-monitor-and-maintain/chapter-43-deploy-and-access-the-monitoring-on-kubernetes/ https://mlops.swiss-ai-center.ch/part-4-monitor-and-maintain/chapter-44-trigger-drift-alerts-with-the-cicd-workflow/ https://mlops.swiss-ai-center.ch/part-4-monitor-and-maintain/chapter-45-review-drift-alerts-and-decide-on-action/ https://mlops.swiss-ai-center.ch/part-4-monitor-and-maintain/conclusion/ https://mlops.swiss-ai-center.ch/part-5-label-data-and-retrain/introduction/ https://mlops.swiss-ai-center.ch/part-5-label-data-and-retrain/chapter-51-set-up-label-studio/ https://mlops.swiss-ai-center.ch/part-5-label-data-and-retrain/chapter-52-label-new-data-with-label-studio/ https://mlops.swiss-ai-center.ch/part-5-label-data-and-retrain/chapter-53-link-the-model-to-label-studio/ https://mlops.swiss-ai-center.ch/part-5-label-data-and-retrain/chapter-54-retrain-the-model-from-new-data-with-dvc/ https://mlops.swiss-ai-center.ch/part-5-label-data-and-retrain/conclusion/ https://mlops.swiss-ai-center.ch/clean-up/ https://mlops.swiss-ai-center.ch/conclusion/