IBM Machine Learning for z/OS
The cognitive platform can continuously create, train and deploy a substantial volume of analytic models at the source
2/15/2017 1:19:48 PM |
By Keelia Moeller
Up until now, data scientists could take days, or even weeks developing and retooling one analytic model, doing so step by step in an overly tedious process. To solve that, IBM announces IBM Machine Learning for z/OS—the first cognitive platform that can continuously create, train and deploy a substantial volume of analytic models at the source of corporate data stores. This can happen in any language, using any transactional data type, from various machine learning framework, all without the risk of moving data off premises.
Putting It Simply
What is machine learning, and how does it relate to cognitive systems? Think about your video suggestions based on what you’ve previously watched, or suggested ads that pop up on your phone after you’ve clicked on a related website. These interfaces collect data to make the user experience more personalized. In the same way, machine learning consumes large amounts of data to generate output across multiple platforms, analytics systems, embedded systems or edge networks.
IBM Machine Learning is now available on z/OS. To learn more about IBM Machine Learning and how you can get started, read the full article
, news release
and machine learning landing page
Read the July/August 2017 issue of IBM Systems magazine, IBM Z,
which focuses on how IBM Machine Learning for z/OS transforms the platform into a cognitive learning system through continuous feedback, which simplifies model retraining. IBM Machine Learning is important and different than anything else, and z Systems is the right platform to take advantage of it.
Dinesh Nirmal, vice president of Analytics Development, IBM, explains how IBM Machine Learning for z/OS continually provides businesses with new ways to learn.
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