Automating the Data Scientist
Talk about a fraught concept, this one ought to give you the willies. I don’t mean to be a Luddite about the magical abilities of technology but the concept here is to replace data scientists with software.
As long as I have practiced in data science I am constantly coming upon new and unexpected reasons that my results may be misguided. As a reminder you might look back at my recent articles on Simpson’s Paradox (read it here) or Why Big Data Isn’t Necessarily Better Data (read it here).
So perhaps even though the most recent NoSQL ML techniques are too directional and not sufficiently specific in their results to lend themselves to automation (or perhaps these are exactly the required conditions), then the question is open as to whether more traditional ML techniques like predictive modeling can be successfully automated. Which opens the door to their application by untrained users, or charitably, “citizen data scientists”.
Tom Simonite takes on this topic in his February article by this same name. The premise he says is this, not enough data scientists to go around means the process must be automated.
Read more at: http://www.datasciencecentral.com/profiles/blogs/automating-the-data-scientist?utm_content=bufferd06a3&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer
Source: Data Science Central