I understand how mind blowing the potential of deep learning is, but the truth is, majority of companies in the world dont care about it, or do not need that level of machine learning expertise.
If we want to democratize machine learning we have to acknowledge the fact the most people Learning all the cool generative neural networks will not end up working for Google or Facebook.
What I see is that most youngsters join this bandwagon of machine learning with hopes of working on these mind-blowing ideas, but when they do get a job at a descent company with a good pay, but are asked to produce "medicore" models, they feel like losers. I dont know when, but somewhere in this rush of deep learning, the spirit of it all got lost.
Since when did the people who use Gradient Boosting, Logistic regression, Random Forest became oldies and medicore.
The result is that, most of the guys we interwiew for a role know very little about basics and hardly anything about the underlying maths. The just know how to use the packages on already prepared data.
Update : Thanks for all the comments, this discussion has really been enlightening for me and an amazing experience, given its my first post in reddit. Thanks a lot for the Gold Award, it means a lot to me.
Just to respond to some of the popular questions and opinions in the comments.
Do we expect people to have to remember all the maths of the machine learning?
No ways, i dont remember 99% of what i studied in college. But thats not the point. When applying these algorithms, one must know the underlying principles of it, and not just which python library they need to import.