- 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
AI Center User Guide
ML packages
This section contains ML Packages examples to help you get started building your own.
process_data. In addition, it offers an example on saving artifacts to pipeline output.
You can download the sample from the following link: Iris Flower Classifier.
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 the following link: Template ML package.
This is an example of an ML Package (non-retrainable) for image classification. It is based on the paper "Rethinking the Inception Architecture for Computer Vision" by Szegedy et al.
You can download the sample from the following link: Inception Image Classification.
