
Machine Learning Field Guide - KamWithK
https://www.kamwithk.com/machine-learning-field-guide-ckbbqt0iv025u5ks1a7kgjckx
======
gavinray
Half of the article is massive, meaningless images. As in, "a girl in the
woods wearing sunglasses staring up at a tree" so big it takes up an entire
length of my screen - massive.

It took me nearly 30 seconds to scroll down the length of it. I counted the
actual lines of code in the article, and it amounts to 27.

The only substance of the article shows loading a CSV file into Python and
using a few SKLearn functions on them, with a handful of paragraphs that
amount to essentially docstrings of the methods themselves without any actual
explanation.

The content on Linear/Logistic Regression, Support Vector Machines, Neural
Networks, Decision Trees, K-Means, and Random Forests all fit in the same
screenlength.

I'm not sure that level of brevity of information is genuinely helpful to
someone.

"Decision trees can be used for regression problems too. Although simple, to
avoid overfitting, several hyperparameters must be chosen. These all, in
general, relate to how deep the tree is and how many decisions are to be
made."

There's no prior given for the context of what a "hyperparameter" is, how it's
different than a parameter, or what the problem of "overfitting" is.

~~~
wltprgm
It does look like a content farm

~~~
gavinray
I mean sure, do what you gotta do I guess for low-grade resume padding if
you're short up on personal recommendations/experience/skills, for job
purposes, but why post it here?

=/

