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Codes and notes on Productionizing Machine Learning Services: experiment tracking (Mlflow), orchestration(Mage, Prefect), deployment(AWS kinesis, lambda, flask ), monitoring (Grafana, Evidently, Prefect), containerize (docker, K8S), CI/CD (Github actions)
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(02-Exp-track) Installed Mlflow, created exp-tracking-env, tuning using Mlflow, model management, and model registry
856a151View on GitHub(01-intro)- experimented predicting duration using LR and lasso as well as saving models
56a5be0View on GitHub7
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