Cloud giant IBM - traditionally known as ‘Big Blue’ - has announced the launch of
IBM Machine Learning. With headquarters in Armonk, New York, United States, IBM is a household name that has moved from being a software and hardware provider to focusing on the cloud. The company acquired Softlayer in 2012 to enhance its cloud capability and it offers a range of services, including ‘Big Data’ solutions. IBM Machine Learning is “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”.
Developing, testing and retooling analytic models traditionally takes a long time. IBM Machine Learning enables data scientists to automate the development of operational analytic models. It leverages IBM Watson’s technology core machine learning capability and makes it available to the ‘z System mainframe’ - a solution that supports many of the world’s enterprises by managing “billions of daily transactions are processed by banks, retailers, insurers, transportation firms and governments”.
IBM Machine Learning supports computing languages such as Scala and Java, Python, and also accommodates Machine Learning frameworks like Apache SparkML, TensorFlow and H2O. It can manage any transactional data type and mitigates the risk of physically moving data away from company premises. The solution also facilitates Cognitive Automation for Data Scientists, which is driven by IBM Research and helps data scientists choose the algorithm they require for the data they are dealing with.
"Machine Learning and deep learning represent new frontiers in analytics,” explained IBM Analytics’ General Manager, Rob Thomas. “These technologies will be foundational to automating insight at the scale of the world's critical systems and cloud services. 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."
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