dotData and customer SMBC @Forbes on the Explosion Of Automated #machinelearning

dotData and customer SMBC @Forbes on the Explosion Of Automated #machinelearning

September 3, 2019

dotData and customer SMBC on the Explosion Of Automated #machinelearning.  Read more about it here: “dotData And The Explosion Of Automated Machine Learning” @Forbes.

AutoML is an automated machine learning framework for analyzing data, generating well-fitting models, and using APIs to help deploy the model into production. AutoML is an automated machine learning tool used by two groups of people: data scientists who have training in machine learning and citizen data scientists. Data scientists may not yet be comfortable with AutoML because they don’t want to use new technology. Because this new field is taking off rapidly, multiple vendors have created offerings for AutoML. Still, the companies focus on different types of users and different parts of the market.

There are two primary users of AutoML: data scientists and citizen analysts. DataRobot, dotData,, and dotDataPy are all aimed at both groups, but dotData Enterprise is aimed at data scientists. In the AutoML field, vendors focus on different aspects of the user sophistication continuum, and the features and functions of their products vary. Each vendor can extract data from multiple data sources and is primarily oriented towards helping enterprises bring about large-scale business transformation with AI.

Sumitomo Mitsui Banking Corporation (SMBC), a Tokyo-based multinational bank, began using dotData’s software in early 2016 for a proof-of-concept project. The bank uses dotData Enterprise to automate its data management process and is having trouble finding enough data scientists to meet the demand. With dotData software, a Sumitomo Mitsui Financial Group branch used ten hours on average to create a model with higher quality. AutoML is changing how firms do machine learning and predictive analytics by making it easier to deploy models into production. Read the rest of the article at Forbes.


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