Cloud Pak for Data#

Requirements#

Starting work with IBM Cloud Pak for Data refer to Getting started section in main product documentation:

Supported machine learning frameworks#

For the list of supported machine learning frameworks (models) of IBM Cloud Pak® for Data, refer to Watson Machine Learning Documentation:

Authentication#

If you are a user of IBM Cloud Pak® for Data version 4.0, you can create an IBM Watson Machine Learning Python client by providing credentials, or using a token:

Note: To determine <URL> and <APIKEY> refer to Authentication section of product documentation.

Example of creating the client using credentials (username/password):

from ibm_watson_machine_learning import APIClient
wml_credentials = {
                   "url": "<URL>",
                   "username": "<USERNAME>",
                   "password" : "<PASSWORD>",
                   "instance_id": "openshift",
                   "version" : "4.0"
                  }

client = APIClient(wml_credentials)

Example of creating the client using credentials (username/apikey):

from ibm_watson_machine_learning import APIClient
wml_credentials = {
                   "url": "<URL>",
                   "username": "<USERNAME>",
                   "apikey" : "<APIKEY>",
                   "instance_id": "openshift",
                   "version" : "4.0"
                  }

client = APIClient(wml_credentials)

Example of creating the client using a token:

In IBM Cloud Pak® for Data version 4.0, user can authenticate with token set in the notebook environment.

access_token = os.environ['USER_ACCESS_TOKEN']
from ibm_watson_machine_learning import APIClient

wml_credentials = {
                   "url": "<URL>",
                   "token": access_token,
                   "instance_id": "openshift"
                   "version" : "4.0"
                  }
client = APIClient(wml_credentials)
Note:

  • The version value should be set to version and release (format: x.y, for example: 4.6) for In IBM Cloud Pak® for Data users.

  • Setting default space id or project id is mandatory. For examples, refer to client.set.default_space() and client.set.default_project() APIs in this document.

Note for IBM Cloud Pak® for Data version 4.0 and above:

If during authentication the following error appear:

Attempt of generating `bedrock_url` automatically failed.
If iamintegration=True, please provide `bedrock_url` in wml_credentials.
If iamintegration=False, please validate your credentials.

There are two possible causes:

  1. During installation were chosen option: iamintegration=False (default configuration). Probably the credentials are invalid or service is temporary unavailable.

  2. During installation were chosen option: iamintegration=True. Autogeneration of bedrock_url wasn’t successful. In this situation IBM Cloud Pak foundational services URL should be provided as bedrock_url param to the wml_credentials.

    To get IBM Cloud Pak foundational services URL please refer to documentation: https://www.ibm.com/docs/en/cloud-paks/cp-data/4.0?topic=overview-authentication#find_bedrock