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On the job experience about which ML algorithm is more useful for a task is certainly helpful.

But, knowing how to implement "X from scratch" gives you far more useful information about how and why a particular algorithm is suitable for a certain task. We should encourage people to reimplement algorithms from scratch (for fun, not production usage) so that they understand how the sausage is made.

Also, SVMs support a whole lot of different loss functions. I suspect that a properly tuned SVM will do better than a properly tuned logistic regression.