Supervised Learning Probabilistic Neural Networks
If deep learning were great, there would be no need to pay people like myself to massage the raw data into a form that is more amenable to shallow learning algorithms. I also don't think history will judge the ability of human feature engineering kindly. Textual data is an exception because it's easy to work with: naive encodings (e.g., bag of bigrams) are a great starting point, and there are many sources of side-information available that can be joined up against tokens. The computer vision community, in contrast, seems to face a much harder problem. Although historically their labeled data sets were small by internet standards, this has been mitigated in recent years due to crowdsourcing and public database definition efforts. So the problem seems to be that pixels are a harder
Source: Machined Learnings
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I again agree with you 110%.
But then there was Mike.
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