This will be the first in a series of tutorials covering a few of the fundamental topics in statistical analysis and machine learning.
K-...
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Is this the same as K Nearest Neighbors or are they different models?
They are different. I do plan to cover K-N-N (K nearest neighbors) in the future. K-n-n can be used for clustering, although its not exactly a clustering algorithm.
Sorry, to many jokes for some simple explanation. The explanation is lost between "faceboook happy system" and broke investors that paid to rebuild bathrooms.
Appreciate the feedback. “to many jokes” is a bit of a subjective thing, but I’m worried that the explanation is lost.
Can I ask if you read the entire post or just the intro? Also which part of the algorithm was poorly explained? (be specific, I’m just want to know how to improve)
Naah the jokes are fine mate. Its your style, don't worry about it!
I personally enjoyed the article as someone who's also an ML dev
Most ML blogs are ridiculously boring so the humour makes it ALOT more palpable
What a great intro to K-Means...congrats Ryland
Wow. Thank you for this article. I wanna do this stuff! I will be following.
Glad to hear you liked it. I will release part 2 next week.
Great article, congratulations!
Glad to hear it!