Normally, you don’t need to be a fortune teller to predict Oscar winners, but the Academy has sprung a few surprises in recent years.

Recently, a team of data scientists tested whether their machine learning model could outsmart the bookmakers — with mixed results.

The boffins behind the BigML machine learning platform made their predictions with a Deepnets model, an optimised implementation of the Deep Neural Networks supervised learning technique.

Its biggest miss was in the hotly-contested best picture category. The model correctly rejected the bookie’s favourite, 1917, to pick an outsider. But it ultimately went for the wrong one, plumping for Once Upon a Time in Hollywood ahead of surprise winner Parasite.

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