5 ms·
It is purely a matter of opinion whether DBNs are "overhyped" but I hope you would agree that they are currently being "hyped". And I hope you understand how th
by spikels 14y ago
It is purely a matter of opinion whether DBNs are "overhyped" but I hope you would agree that they are currently being "hyped". And I hope you understand how this can actually damage the potential of what is likely some very good technology like say like what happened to neural nets. :)
It is also a matter of opinion how widely they are being used in industry. Certainly they are being studied in many companies but they do not a appear to used much in production because of their complexity and high training cost. This is still cutting edge technology.
In my experience most professionally trained mathematicians and statisticians are still pretty skeptical of these claims. Wouldn't you agree?
- stiff 14y agoIt is OK to be skeptical, all I am trying to say is that most of the comments leave the impression of the poster trying to lean over backwards to say something at all related to the topic, often ending up with generic truisms. For example how is model building being a small part of practical ML criticism of deep learning? How is it on-topic at all?
- spikels 14y agoNot my comment but I think they mean that it is a relatively small part of the overall process and thus not "The Biggest Data Science Breakthrough". Maybe not a fair criticism but they have a point. I would love to see a breakthrough in data cleansing or how about just standardized coding, labeling and formatting. Unfortunately I've used lots of 3rd party data sources and wasted more time on these brainless activities than I want to think about. Consider yourself lucky if you only work on web logs where you control what they look like.
- deleted 14y ago[deleted]