Discover and read the best of Twitter Threads about #traditionalml
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Deep Learning and Neural Networks have become the default approaches to Machine Learning in recent years. However, despite their spectacular success in certain domains (vision and NLP in particular),
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their use across the board for all ML problems and with all datasets is problematic, to say the least. Oftentimes better and more robust results can be obtained with simpler, easier to train and deploy, classical ML algorithms.
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One such “traditional” approach was recently used to reevaluate sleep scoring on a few publicly available datasets. The results were published in the journal of Biomedical Signal Processing and Control.
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