[durbatuluk]

I should start calling myself a ML expert? I'm 32 year old and most of these "ML algorithms" are called statistics for me. Maybe I'm missing something, where is the LEARNING on k-means? Numerical solutions seems to be on rise now.

Nice write for someone starting, more details about details of algorithm steps would greatly attract more readers.

[Rainymood]

>I should start calling myself a ML expert? I'm 32 year old and most of these "ML algorithms" are called statistics for me. Maybe I'm missing something, where is the LEARNING on k-means? Numerical solutions seems to be on rise now.

Yes, you can. I have studied statistics and I cringe at the watering down of what "machine learning" and "AI" has become; simple statistics.

>Nice write for someone starting, more details about details of algorithm steps would greatly attract more readers.

I disagree, making it even simpler would attract more readers. You see the same with Youtube tutorials that have 22 parts. The first part has 200.000 views, the second 150.000 and the 20th part only has 400 views or so.

[th0ma5]

Some of the simpler stuff sure, but more advanced techniques may require more understanding of more complex data and relationships. A lot of this is like you suspect and straightforward. It is being automated by things like AutoML. But doing things "better" for some definition of it is always probably going to be an expert thing. K-Means like this article outlines is maybe a beginner thing? I guess you could get complicated with it though as well.