Using SVM

Using SVM

I'm still not entirely sure, should I use this algorithm or that algorithm, that's actually okay.

When I face a machine learning problem, you know, sometimes its actually just not clear whether that's the best algorithm to use, but as you saw in the earlier videos, really, you know, the algorithm does matter, but what often matters even more is things like, how much data do you have.

And how skilled are you, how good are you at doing error analysis and debugging learning algorithms, figuring out how to design new features and figuring out what other features to give you learning algorithms and so on.

And often those things will matter more than what you are using logistic regression or an SVM.

But having said that,the SVM is still widely perceived as one of the most powerful learning algorithms, and there is this regime of when there's a very effective way to learn complex non linear functions.

And so I actually, together with logistic regressions, neural networks, SVM's,

using those to speed learning algorithms you're I think very well positioned to build state of the art you know, machine learning systems for a wide region for applications and this

is another very powerful tool to have in your arsenal.

One that is used all over the place in Silicon Valley, or in industry and in the Academia, to build many high performance machine learning system.