Given the way such models are constructed, this is not unexpected. For some time humans will still be needed to guide the process. In particular to understand the link to business process.
How machine learning creates demand for human workers in Techrepublic
Building a slide deck, pitch, or presentation? Here are the big takeaways:
An automated machine learning platform called Auto Tune Models (ATM) from MIT and Michigan State University uses cloud-based, on-demand computing to speed data analysis. -MIT and Michigan State University, 2017
ATM was able to deliver a solution better than the one humans had come up with 30% of the time, and could do this 100x faster. -MIT and Michigan State University, 2017
A new automated machine learning system can analyze data and come up with a solution 100x faster than humans, according to a new paper from MIT and Michigan State University. This could potentially help businesses take advantage of machine learning's capabilities in a faster, easier way, while also filling data science talent gaps.
The system also potentially marks a tipping point in machine learning adoption in the enterprise, which is expected to double in 2018, as TechRepublic's sister site ZDNet reported.
When seeking a solution to a problem, data scientists must wade through huge datasets, and choose the modeling technique they believe will work best. The issue is, there are hundreds of techniques to choose from, including neural networks and support vector machines, and choosing the best one could potentially mean the difference between millions of dollars in ad revenue or none, or catching a flaw in a medical device or not ... "
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