-
Install required dependencies
-
Start training
python mnist_classifier.py
.This will download MNIST dataset to the current directory, create
mlruns
folder for storing training experiments logs, checkpoints and starts training. -
Run
mlflow ui
to open mlfow dashboard and track training history. -
Run
mlflow models serve -m mlruns/0/<run id>/artifacts/model -h 0.0.0.0 -p 8001
to deploy the trained model.The deployed model can be used using CURL or the implemented client inside
mnist_classifier_client.py
.
mlflowmnist's Introduction
mlflowmnist's People
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