What will you learn?
How you can reproduce previously tracked experiments in Neptune.
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Fetching the run data in Neptune
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Customizing the runs table
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Resuming the run in Neptune
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Assigning the same data version to the run
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Downloading the hyperparameters from the run
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What will the results look like in the Neptune UI?
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What is the logic for waiting (run.sync()) after doing some commands?
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How to monitor the model through different phases of the MLOps lifecycle?
Important: This video was created in February 2022. For the most up-to-date code examples, please refer to the Neptune docs.
Other useful resources
See also how to resume a run.
More about How to Reproduce Previously Tracked Experiments
See also
What is a Project in Neptune?
See also
Model Training: Detectron2 + neptune.ai Integration [Example]
See also
Model Training: Prophet + neptune.ai Integration [Example]
See also
Create AzureML Pipeline – Workshop with Aurimas Griciūnas
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