[atum47]

That's a really cool initiative, but I think we disagree on the term "from scratch". Taking a look at the source code, I see you're using sklearn - which is a great tool - but, from scratch, at least for me, implies writing your own code (logistic and linear regression, adaline, perceptron, mlp, knn, kmeans...) I mean, that's how I learned it. But again, congratulations on the initiative.

[dafrdman]

Perhaps I should have been clearer, but the "code" section within each chapter is not "from scratch". The "construction" section is "from scratch" in that it only uses numpy (not scikit learn). The scikit-learn part is just so new users can see how these could be fit in practice.

[Bedon292]

I went straight to the "code" section. Didn't know there was stuff in the "construction" section too. I would definitely consider not using sklearn for anything other than data sets. You already defined them, why not use them? Or rename the "code" section. I expected that to be the final code as you build it. Maybe show the usage of both side by side, as a way to ease people into sklearn. But the "code" section should totally be focused on what you made.

[dafrdman]

That's sensible. Maybe change construction to code and code to application? Or keep construction but rename code? I'll have to brainstorm. I definitely don't want people missing the construction section so this is great feedback. Thanks!

[Bedon292]

I like the sound of Application at least. Or 'In practice'?And Construction does make sense when I think about it more. Not sure I can think of a better name at least.

[dafrdman]

My hesitance with "Application" is that sounds like I'm going to use some interesting dataset or do some cool project (and this is essentially using iris to build basic models). How about "code" becomes "implementation"?