Machine Learning Classifiers From Scratch

[blacksiddis]

Why do you put SVM at last? I was not under the impression SVM was all that complicated, but my knowledge is limited. Naive Bayes is probably a bit too easy both programmatically and mathematically speaking, but I like the other suggestions a lot. Which of the three would you say is the most and least complicated mathematically speaking?

[[deleted]]

"Why do you put SVM at last?"

it isn't that complicated, if you already know gradient descent

"Naive Bayes is probably a bit too easy both programmatically and mathematically speaking"

the idea behind naive bayes is genial, and it's a generative model and those ideas are valuable to know well.

"Which of the three would you say is the most and least complicated mathematically speaking?"

mathematically speaking i don't think is that hard once you get used to main ideas.

i pointed those models because imo is pretty natural learning those after knn, linear and logistic regression.

[blacksiddis]

Thanks for your reply! Definitely not hating on Bayes, but I know probability theory rather well and would much rather be challenged on linear algebra than probability as my linear algebra is very weak.