IBM Corp. is no novice to the tech game, and the company sees its next move as evolving machine learning models and predictive analytics.

“We have been in predictive analytics for a long time,” said Dinesh Nirmal (pictured), vice president of analytics development, IBM Analytics, at IBM, sharing his company’s latest efforts to convert this longstanding interest into viable business.

Nirmal recently joined Dave Vellante (@dvellante) and Stu Miniman (@stu), co-hosts of theCUBE, SiliconANGLE Media’s mobile live streaming studio, during the IBM Machine Learning Launch Event in New York, NY. They discussed how to build and deploy a machine learning model, among other hot topics. (*Disclosure below.)

With its machine learning platform, IBM is bringing in flexibility so that customers can use whatever software language or execution engine they prefer. The platform also contains a new collaborative piece to facilitate productivity between organizations, Nirmal stated.

Additionally, IBM has introduced a feedback loop for models. When a model is deployed, it will have two endpoints: a uniform resource identifier to plug in the applications on one end, and a feedback loop on the other end. This makes any future retraining of the model much easier and faster.

‘Fun vs. elbow grease’

For all the work IBM is doing to promote machine learning as a service layer, Nirmal pointed out the importance of starting with clean data for deploying the model to train a machine. “When you look at machine learning, you have data, which is the most critical piece to building or deploying the model. A lot of times, the data itself is not clean,” he explained.

“Machine learning is 20 percent fun and 80 percent elbow grease,” he joked, saying that a great deal of the 80 percent is around cleaning the data, preparing it for model ingestion.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of the IBM Machine Learning Launch Event 2017 NYC. (*Disclosure: TheCUBE is a media partner at the conference. Neither IBM nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo by SiliconANGLE