This sample Watson Studio project demonstrates the capabilities of the Watson Studio Pipeline editor. Use a pipeline to automate the end-to-end AI lifecyle, from loading data, training models, selecting the best result, and deploying the best model to a deployment space. You create and configure the flow once, and then run it on demand or on a schedule, without having to interact with individual tools and assets.
In this sample, a pre-populated project is added to Watson Studio for you. Use the sample pipeline to:
- Copy sample assets into a space.
- Run a notebook and an AutoAI experiment simultaneously, on a common training data set.
- Use another notebook to compare the results and select the best model, ranked for accuracy.
- Create a web service deployment for the selected model.
- Export selected model to a location in the COS.