developerWorks cognitiveIBM recently announced that it is bringing IBM Machine Learning to the private cloud.

IBM has extracted the core machine learning technology from IBM Watson and will initially make it available where much of the world’s enterprise data resides: the z System mainframe, the operational core of global organizations where billions of daily transactions are processed.

This will be the first cognitive platform for continuously creating, training and deploying a high volume of analytic models in the private cloud at the source of vast corporate data stores.

IBM Machine Learning allows data scientists to automate the creation, training and deployment of operational analytic models that will support:

  • Any language (eg. Scala, Java, Python)
  • Any popular Machine Learning framework like (eg. Apache SparkML, TensorFlow, H2O)
  • Any transactional data type
  • Without the cost, latency or risk of moving data off premise.

Cognitive Automation for Data Scientists from IBM Research will assist data scientists in choosing the right algorithm for the data by scoring their data against the available algorithms and providing the best match for their needs. The service also considers various circumstances – such as what the algorithm is needed to do and how fast it needs to produce results.

“Machine Learning and deep learning represent new frontiers in analytics. These technologies will be foundational to automating insight at the scale of the world’s critical systems and cloud services,” said Rob Thomas, General Manager, IBM Analytics. “IBM Machine Learning was designed leveraging our core Watson technologies to accelerate the adoption of machine learning where the majority of corporate data resides. As clients see business returns on private cloud, they will expand for hybrid and public cloud implementations.”

IBM Machine Learning will first be available on z/OS and will be available for other platforms in the future, including IBM POWER Systems.

To learn more about IBM Machine Learning, please visit:


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