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Machine Learning in Digital Process Automation — Part II by Ralf Mueller

Blog: PaaS Community

In this second part of the ML in Digital Process Automation article series, we focus on how to consume a Machine Learning Model created in Autonomous Data Warehouse (ADW) for scoring in Integration Cloud Processes. It is assumed that the reader is familiar with the content of Part I. For this article we assume an existing ML model stored on Object Storage. We will give step-by-step instructions on how to bring such models into Oracle Integration Cloud and use them in process automation.

By the time of this writing, the Machine Learning functionality for Integration Cloud Process Automation is in “Limited Availability” mode and must be enabled by a feature flag. Please get in touch with your Integration Cloud representative to get this feature enabled for your Integration Cloud instance.

OML Micro-Services

Oracle Integration Cloud comprises of a new set of micro-services for Machine Learning, the Oracle Machine Learning (OML) micro-services developed by the OML team in Oracle Advanced Analytics organization as part of the Oracle Machine Learning Platform. We will give an in-depth overview of OML micro-services in a later article, for now, it is sufficient to understand the functionality coming with OML micro-services

Cognitive Text Services
Cognitive Text Services provide Machine Learning functionality for Text Classification, Keywords, Summary, Similarity, and Sentiment Analysis. The underlying ML models are pre-trained by Oracle and can be used out-of-the-box. Typical examples in digital process automation include giving a summary of a large text document or give sentiment on customer input.
Cognitive Image Services
Cognitive Image Services provide Machine Learning functionality for Image Classification, NSFW content and Image Similarity. Like with the Cognitive Text Services, the underlying ML models are pre-trained by Oracle. Read the complete article here.

PaaS Partner Community

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