AiTEMS scenarios

Available in Classic and VPC

Through NAVER Cloud Platform's AiTEMS, you can use customized recommendation services without machine learning knowledge. You can see how to use it in detail in Getting Started with AiTEMS and Using AiTEMS, but we recommend that you first go through the full scenario of using AiTEMS. Reading the guide after learning the usage scenario will allow you to use AiTEMS more efficiently. The overall sequence of using AiTEMS and description of each sequence are as follows.

1. Set usage permissions
2. Create service
3. Create schema
4. Create dataset
5. Connect dataset
6. Proceed with learning
7. Test learning results

1. Set usage permissions

If you need to manage and share AiTEMS with multiple users, you can set the permissions by each user. Permissions for each user can be configured either as an administrator or a user through Sub Account of the NAVER Cloud Platform. Since setting usage permissions is not mandatory, you can set or remove them at any time whenever new permission is required while using AiTEMS.

See the following guides:

• Managing AiTEMS permissions
• Sub Account user guide

2. Create service

Create a service, which is the basic unit for using AiTEMS. You can proceed and manage learning by service. See the following guides:

• Create service

3. Create schema

Create a schema by configuring the schema fields identical to the fields in the dataset file to be learned on. You can create schema either as new or by cloning an existing schema, and you must create one for each dataset type. See the following guides:

• Create schema
• Duplicate schema

4. Create dataset

Create a dataset by uploading a dataset file to be learned and linking it with the schema. You must create one dataset for each type. See the following guides:

• Create dataset

5. Connect dataset

Connect the created dataset to the service. You can connect only datasets that have been successfully uploaded to the service, and if the upload fails, you can retry uploading the dataset file. Learning can be performed with datasets connected to the service. See the following guides:

• Connect dataset
• Upload dataset

6. Proceed with learning

Learning proceeds with the connected dataset. Learning can proceed according to the recommendation type, and the optimal learning model can be implemented through HPO settings. See the following guides:

• Proceed with learning

7. Test learning results

When learning is complete, the results are tested to ensure learning was successful. See the following guides:

• Test learning results