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sefiks.com | ||
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p.migdal.pl
To err is human... and machine, alike. Overfitting, adversarial examples, optical illusions, hallucinations, Freudian slips, etc. |
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stribny.name
Fields in Artificial Intelligence and what libraries to use to address them. |
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erikbern.com
From my presentation at MLConf, one of the points I think is worth stressing again is how extremely well combining different algorithms works. In this case, we're training machine learning algorithms on different data sets (playlists, play counts, sessions) and different objectives (least squares, max likelihood). |
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shahpreetk.com
MSc in Computer Science |
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