I find support vector machines better than neural networks using MATLAB apps for classification problems, is that correct?

Is model one better than the previous question was like that. Also, this really depends on the situation. Right. So support vector machines, of course, are more models that have fewer parameters to learn. It works much better if you have a lesser amount of data. But as neural networks, usually deep neural networks have many, many trainable parameters. And they do better if you have large amounts of data, that you can really drive down the model bias to very small values. Okay. I don't know about MATLAB apps, I have not used them myself. So this is the basic idea. If you have if you're working in a low data regime, then using models like support vector machines, or SPM. It makes sense. If you're working with large amounts of data, then neural networks make sense. Typically, when we have rich media, so let's say you take images or speech or language, these are high dimensional data sets, right? In such cases, neural networks is the only option we have, we typically almost have defaulted to using deep neural networks for these cases, if you have a much more low dimensional data, maybe you have a small table with five columns given to you and you need to predict the six columns, since things like support vector machines