TEDxBocaRaton 2022: 'Defining Moments' (Jan. 29th)
How Feature Stores Can Accelerate Your Path to Scalable MLOps
Wednesday, January 19th, 2022: 12:00 PM to 1:00 PM
Virtual

Features are individual measurable independent variables of a phenomenon to be predicted. When building a statistical model of that phenomenon, data scientists must select the features best suited to reducing the model's computational cost and boosting its predictive accuracy. Feature selection is a core responsibility for data scientists. It involves identifying which features in the data best predict some quantifiable outcome of interest. To the extent that data scientists can reuse previously discovered features in future machine learning (ML) projects, they can streamline and accelerate the process under which statistical models are built, trained, and deployed into production.

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