The following sections describe alternative workflows for a variety of specialized data types:
|Composable ML||Build custom blueprints using built-in tasks and custom Python/R code.|
|Unsupervised learning||Work with unlabeled or partially labeled data to detect patterns, such as anomalies and clusters).|
|Visual AI||Apply visual learning to image data.|
|Location AI||Use geospatial analysis on spatial data.|
|Bias and Fairness||Access an index page for quick links to all Bias and Fairness content.|
|OTV||Date/time partitioning for non-time series modeling.|
|Multilabel modeling||Perform modeling in which each row in a dataset is associated with one, several, or zero labels.|
Updated March 8, 2022
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