I’m branching out. I’m shifting focus onto the pursuits of passion for machine perception, a subset of machine learning. While I’m far from expert, I’ve developed a pretty good ground-up understanding of the origins, components, and applicability of the recent well-deserved and over-hyped craze of deep learning.

Which segues right into the main point of this post. It’s not about code or a specific technique for applying some cool machine learning thing I discovered. No, it’s more political than that. It’s about attitudes like this:

Post content: well, it's pretty obvious that we are dealing with too many tutorials like: "how to build a deep learning model", or "a simple guide to machine learning" and so.. please go and learn algebra and only after you get the principals of  equations, functions and factorization study derivatives and integrals to understand a function's rate of change and how to calculate the area under a curve and why(!!) before delving into statistics & probability and machine learning... otherwise, you are only doing hyper-parameters tuning or using a library like TensorFlow...

I get it. There’s a lot of hype and a lot of padding when it comes to what machine learning is and can do and who gets to call themselves an expert or even an engineer in the field.

And I’ll admit, there’s a certain part of me that reacted with “Hey, I know algebra! And factorization, derivatives, differential equations, calculus, stati…” you get where I’m going. High five, bro. Cerebral high five from our huge brains!!!

But I also had a much stronger, visceral, and longer lasting reaction:

“What utter rubbish.”

It’s false pride and elitism at its most insidious. And it’s bad for progress.

If someone wants to build something using packaged machine learning tools like TensorFlow with an out-of-the-box model that she read somewhere will work well for her use case, what exactly is wrong with that? Will it be advancing the ground of fundamental machine learning as a discipline? No. Will it build something cool, useful, or beneficial to the world? Maybe. So what’s the problem? Build it! Have fun! Learn something! Make something!

There’s a rich ecosystem of ideas to be realized, of practical problems to be solved. There’s no reason to attempt to bar people from doing so, from focusing their energies on a domain that inspires them, just because you’re really proud of how smart you are in the things that you happen to know. It’s all progress, and it’s progress that would not and could not happen if this sort of discouragement were taken to heart.

I’m left wondering if the fellow who posted this truly has a deep understanding of all of the aspects of electromagnetics, RF and satellite communications, orbital dynamics, web server infrastructure, web traffic load balancing, device manufacturing, UX design, product management, employment economics, and so on, all of which were necessary for him to be able to make that post on a mobile phone using an immensely popular profession social networking app. Maybe he should learn those before delving into posting on LinkedIn.