ai-center
2024.10
true
- Release Notes
- Before you begin
- Getting started
- Installing AI Center
- Migration and upgrade
- Projects
- Datasets
- Data Labeling
- ML packages
- Out of the box packages
- Pipelines
- ML Skills
- ML Logs
- Document UnderstandingTM in AI Center
- AI Center API
- How to
- Licensing
- Basic Troubleshooting Guide
ML packages
AI Center User Guide
Last updated Nov 11, 2024
ML packages
This section contains ML Packages examples to help you get started building your own.
This is a sample ML Package for the archetypal Iris Flower dataset. The ML Package is retrainable and offers an example on
how to split data into training and testing in
process_data
. In addition, it offers an example on saving artifacts to pipeline output.
You can download the sample from here.
This is a template/boilerplate ML Package. The ML Package has all the functions needed to deploy and train however, it does not do anything functional. It is meant to be informative and can be used as a template to start building your own ML Packages. Like Iris Flower Classifier it shows an example on how to split data and save artifacts. This package also shows one way in which a model with transfer learning might be structured.
You can download the sample from here.