Tracking data science assets in Azure ML Studio
Within the assets section, you can track all the components that are at the heart of machine learning operations. Every data science project has the following assets:
- Datasets is where you can find registered datasets. This is a centralized registry where you can register your datasets and avoid colleagues having to work on local copies of the same data or, even worse, subsets of this data. You will work with datasets in Chapter 4, Configuring the Workspace.
- Experiments is a centralized place to track groups of script executions or runs. When you are training a model, you are logging various aspects of that process, including metrics that you might need to compare performance. To group all attempts under the same context, you should submit all the runs under the same experiment name; then, the results will appear in this area. You will work with experiments in Chapter 5, Letting the Machines Do the Model Training.
- Pipelines...
