Support Vector Machines vs Deep Learning Models
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Deep learning models are popular but have some drawbacks in that they’re expensive to train and maintain.
In some contexts, using other simpler models may make more sense. One possible alternative for classification problems are support vector machines (SVM).
When are SVMs preferable to deep learning models?
What are the pros and cons of using an SVM compared to deep or non-deep learning classification models (such as logistic regression)?
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