New Podcast below, by SAS and DSC. Good topic. The question should be: How many and how should the be involved in an enterprise? Just like Computer Scientists, Economists, Statisticians ... and other technical fields. Machine Learning can't do it all.
Do We Need Data Scientists in Today’s World of Automation?
Machine learning is said to be an important driver of the future of intelligent systems, automatically analyzing data and distilling new knowledge, actionable insights and compelling decisions. But why show market trends that investments in data scientists – those golden people that train machine learning models – have never been higher if machine learning can be fully automated? Why do we need data scientists if machine learning is designed to do it all?
In today’s Data Science Central podcast, Véronique Van Vlasselaer, Data & Decision Scientist at SAS, will discuss what machine learning automation entails, and how valuable human input in the machine learning process is.
Speaker: Véronique Van Vlasselaer, Data & Decision Scientist - SAS
Hosted by: Rafael Knuth, Contributing Editor - Data Science Central
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