IBM Opens First Machine Learning Hub in India

New hub in Bengaluru is designed to provide hands-on training in ML and data science to empower organizations to improve business performance

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IBM announced the opening of its first Machine Learning (ML) Hub in India.

The hub, located in Bengaluru, is a physical space for organizations to visit for hands-on training on ML. While there, they’ll learn from, and collaborate with IBM experts to build and deploy analytic models for a new generation of intelligent applications that learn as they are used.

The Bengaluru ML Hub adds to the company’s growing stable of ML Hubs, currently operating in Toronto, San Jose, California, at IBM’s Silicon Valley Lab, Beijing, and Boblingen, Germany. Through the Hubs, data professionals, business analysts and engineers work with IBM data science experts to understand and master the leading tools, technologies and techniques needed to visualize, analyze and interpret data. IBM experts also help visitors build and test rapid, scalable prototypes for fast deployment of their models on their organizations’ enterprises.

The hub also provides a platform for like-minded enterprises to collaborate and transform their data science processes.

Machine Learning is gaining popularity to deal with increasingly complex data and analysis problems. By 2018, 75 percent of enterprise and ISV development globally will include cognitive/Al or machine learning functionality in at least one application, including all business analytics tools.

In addition, Gartner forecasts highest growth in India IT spending in software and IT services for 2017, which includes building new digital platforms with ML and Artificial Intelligence at the center.

IBM ML continuously creates, trains and deploys a high volume of analytic models to Z system mainframes, a system at the operational core of global transactional processes across retail, banking, insurance and transportation. This is essential as the data scientists (least available among today’s IT skills) – might spend days or weeks developing, testing and retooling a single analytic model. IBM ML 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.


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