A number of trends have converged recently to make machine learning (ML) more desirable and practical than ever:
However, embracing machine learning successfully is challenging due to the non-trivial data requirements to deploy ML solutions. During development, creating a functional ML model requires large volumes of diverse data. In production, a deployed ML model still requires voluminous data to learn and improve over time. In turn, managing big data for machine learning demands a robust data management infrastructure and tool portfolio.
In this TDWI webinar, you will learn about:
Date: May 31, 2018
Time: 9:00AM PT
Individual, Student, & Team memberships available.