Global Big Data Conference

As more companies roll out digital infrastructure, they are ingesting greater volumes of data that can be used by business analysts to gauge customer intent and boost transactions. Complexity and lack of data scientists have made that transition harder for mid-size firms looking to monetize "dark" data. Machine learning vendors are therefore automating key aspects of data science workflows that would allow domain experts to customize pipelines and algorithms based on specific data types. AutoML approaches are promoted as boosting the quantity and quality of machine learning models produced on, say, a monthly basis. That's among the goals of a new AutoML platform unveiled this week by Stradigi AI.