The 10 Algorithms Machine Learning Engineers Need to Know
James Le

Interesting to see the class of all clustering algorithms on a list of “need-to-know” ML algorithms. I’m sure you have thoughts on specific algorithms you’d recommend to a beginner, like k-means or k-nearest neighbors?

I also agree with Jeetendra — neural networks probably shouldn’t fall under unsupervised. They arguably deserve their own blog post, since they are essentially function approximation algorithms, and thus generalize to all sorts of problems very well.

Finally, I believe we’ve arrived at a point where SVMs don’t belong on this list. They’ve certainly fallen out of favor in most applied settings relative to, say, ensemble methods or regularized regression.