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During the public Kaggle competition "IceCube -- Neutrinos in Deep Ice",thousands of reconstruction algorithms were created and submitted, aiming toestimate the direction of neutrino events recorded by the IceCube detector.Here we describe in detail the three ultimate best, award-winning solutions.The data handling, architecture, and training process of each of these machinelearning models is laid out, followed up by an in-depth comparison of theperformance on the kaggle datatset. We show that on cascade events in IceCubeabove 10 TeV, the best kaggle solution is able to achieve an angular resolutionof better than 5 degrees, and for tracks correspondingly better than 0.5degrees. These performance measures compare favourably to the currentstate-of-the-art in the field.

IceCube -- Neutrinos in Deep Ice The Top 3 Solutions from the Public Kaggle Competition