Automating the AI life cycle using Cloud Pak for Data
After an organization has been able to collect its data and organize it using a trusted governance catalog, it can now tap into the data to build and scale AI models across the business. To build AI models from the ground up and scale it across the business, organizations need capabilities covering the full AI life cycle, and this includes the following:
- Build—This is where companies build their AI models.
- Run—After a model has been built, it needs to be put into production within an application or a business process.
- Manage—After a model is built and running, the question becomes: How can it be scaled with trust and transparency? To address complex build and run environments, enterprises need a tool that not only manages the environment but also explains how their models arrived at their predictions.
Let's exercise Model Operations (ModelOps) using Cloud Pak for Data to understand...
