I wouldn't wouldn't go so far as to say "dismissed," but they was definitely a period or two when they weren't as shiny. When I did my M.S. reasearch in 2010 S

I wouldn't wouldn't go so far as to say "dismissed," but they was definitely a period or two when they weren't as shiny. When I did my M.S. reasearch in 2010 SVMs were far more popular than neural networks. Deep learning was just over the horizon and most people had given up on it being useful for learning real world problems. We had proven that NNs could learn anything given enough data and the right structure, but the hard part in real life was having enough data and finding the correct structure. So SVMs seemed more robust with available datasets, and most people used those. There were/are several other popular methods, like nearest neighbors and tree-based methods, and NNs just weren't as sexy as they seemed in the late 80's.