Dashboards for Different Stages of the ML Project
We prepared an example set of dashboards to show you how you can use custom dashboards for different stages of the Machine Learning project.
-> Not sure what a custom dashboard in Neptune is? You’ll find this info below.
We created four different dashboards:
1. Data dashboard that includes:
- Dataset versions
- Dataset samples
Check the example project with all those dashboards in the app (no registration needed).
2. Training dashboard that includes:
- RMSE and MAE for training and validation
- RMSE and MAE test scores
- Plots of decision trees
- Feature importance plots
- Training parameters
Check the example project with all those dashboards in the app (no registration needed).
3. Finetuning dashboard that includes:
- RMSE and MAE for training and validation
- RMSE and MAE test scores
- Plots of decision trees
- Finetuning parameters
Check the example project with all those dashboards in the app (no registration needed).
4. Production dashboard that includes:
- Drift score
- Model version
- Pickled model
- Dataset version used for the model
Check the example project with all those dashboards in the app (no registration needed).
When is such a set of dashboards useful?
When you want to track and analyze different metadata for different project stages.
Custom dashboards in Neptune
When analyzing your metadata in the Neptune app, you can create custom dashboards.
They let you combine different metadata types (metrics, parameters, plots, dataset samples, etc.) in a single view.
Why would you need dashboards?
- To see all metadata related to a specific part of the project in one place,
- To see training and validation results on one chart,
- To see validation metrics and image predictions on a subset of a validation set next to each other,
- To divide metadata by stages of the project and display each group in a different dashboard,
- To analyze the same group of charts weekly or for each of your projects, for example, when you want to have a template dashboard to check it every time and/or to show it to other stakeholders
These are the most common use cases that we hear about from our users.
But for sure, these are not the only use cases. We call them ācustomā dashboards for a reason – you can set them up however you want.
How to create a custom dashboard?
Hereās documentation that explains how to create a custom dashboard in the Neptune app.
Other useful resources
See other example dashboards in the Neptune app (including time series prediction dashboards, Reinforcement Learning dashboard, and more).
Watch the webinar From Training to Production: How to Fit Neptune in Your Machine Learning Model Lifecycle?
More about Dashboards for Different Stages of the ML Project
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 GriciÅ«nas
Explore more resources:
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Couldnāt find the use case you were looking for?
Just get in touch, and our ML team will create a custom demo for you.
