Navigating Predictive Learning¶
MindSphere Predictive Learning opens from the main menu, which looks like this:
Here is a brief description of MindSphere Predictive Learning functionality:
MindSphere Tool Bar: click the icon in the top right corner to log out of Predictive Learning.
Predictive Learning Tool Bar: click the user icon to access your user profile. Click the question mark to access Predictive Learning Help or Support.
Import IoT Data: use this page to import your IoT data from various connected devices. An import job is created that you can access anywhere datasets are available.
Manage Imports: shows all IoT import jobs you created and their status. Also allows you to delete any import jobs you no longer need.
Manage Files: use this page to upload your data files from your local machine to an S3 bucket, and then download the files from the S3 bucket to your local machine. You can also view a list of files and folders and perform various actions on those files and folders.
Manage Datasets: once you create a dataset, it resides in a table that displays statistics about all of the datasets you have created or have access to. On the Manage Datasets page, you can open, rename, share, or delete datasets.
Manage Spark Pipeline Models: provides a list of all Spark models you have created in the MindSphere Predictive Learning app, and provides details about each.
Manage Analytics Workspaces: on this page, you can view and open all the existing workspaces, create new workspaces, or delete those you no longer need. You can also start a cluster, open a workspace, add exploration and transformation panels, and launch external services.
Usage Metrics: lets you see how many MindSphere Predictive Learning compute hours remain for your organization, and lists your individual transactions and the number of compute hours you have used.
Manage Environment Configurations: allows administrators to create, update, delete, or view a list of environment configurations based on an available configuration template.
Manage Environments: provides a list of environment configurations created and saved by your administrator and allows you to select and start or stop an environment to run your model on.
Manage Analytical Models (External): use this page to upload models developed outside of Predictive Learning and store them in an external S3 bucket.
Run and Manage Jobs: use this page to select a model and execute the job. You can also view a list of jobs you have run and the details about each.
Manage Jobs with schedule: here you can define jobs that are managed by schedules.
Manage Sources: in this page you can define various data sources for your jobs, based on how you intend to use them, that is, as sources for input or output.
Any questions left?
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