IBM today announced IBM Machine Learning, 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. Even using the most advanced techniques, data scientists in shortest supply among today`s IT skills1 might spend days or weeks developing, testing and retooling even a single analytic model one step at a time.
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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 by banks, retailers, insurers, transportation firms and governments.
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IBM Machine Learning allows data scientists to automate the creation, training and deployment of operational analytic models that will support:
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* Any language (eg. Scala, Java, Python),
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* Any popular Machine Learning framework like (eg. Apache SparkML, TensorFlow, H2O)
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* Any transactional data type
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* Without the cost, latency or risk of moving data off premise.
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IBM Machine Learning also for the first time deploys Cognitive Automation for Data Scientists from IBM Research to 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.
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Clients are beginning to see the value in IBM Machine Learning for z/OS. Argus Health, a DST company, is evaluating this technology to help payers and providers better manage the increasing complexities and optimize outcomes. Argus is testing scenarios applying IBM Machine Learning for z/OS, while exploring creation, training and deployment of applications that can help them better manage pharmacy costs. By using this technology, Argus…