1. Apparently modeling is a solved problem. No need for any knowledge of math/stats folks, just use the latest python packages.
2. Data collection is more important than actually knowing how a model works and even more importantly doesn't work. What happens when he is hired and can't put together a reliable model?
I think his approach is solid (using projects to learn and being ambitious), but it feels like trying to run before you can walk.
It was the narrative the article was pushing about how knowledge of the field doesn't matter, just strong work ethic and selling yourself visually to potential employers.
However, there's some good advice: - get real data
- clean it, play with it, build models
- focus on the cleaning, as that's what the gig normally is (and damn right too, your models will be way better if you've taken the time to understand your data).
I did find the and then he got a job part annoying, but the post was much better than I expected (relative to other towardsdatascience posts).
When I tried to learn how to golf a lot of time was spent on proper form and club choice, not just "swing!" I swung as much without a ball in front of me as with one.
the club is just the component you need to launch the ball towards the hole using your skill. you don't need or want to know what the club is made of until you think of buying a more expensive club(which might be never)
For me it feels more like "software plumber".
Though I admit - I love "software plumber" and want that as a job title some day! Sounds very cyber-punk
Closing those gaps in not just accuracy, but also generalization is the data science portion of the task (and requires much more knowledge than what is demonstrated by this blog post - although they could of left out a lot of detail). They make it seem like if he just had a little bit more time this would of been straightforward. But I am not sure about that.
I am all for giving junior practitioners a chance. But this is like hiring an english major for aerospace engineering because they built a model airplane in my opinion. But maybe I vastly underestimate the amount of extremely low hanging fruit out there for ML projects.