  The IceCube South Pole Neutrino Observatory is a Cherenkov detector
instrumented in a cubic kilometer of ice at the South Pole. IceCube's primary
scientific goal is the detection of TeV neutrino emissions from astrophysical
sources. At the lower center of the IceCube array, there is a subdetector
called DeepCore, which has a denser configuration that makes it possible to
lower the energy threshold of IceCube and observe GeV-scale neutrinos, opening
the window to atmospheric neutrino oscillations studies. Advances in physics
sensitivity have recently been achieved by employing Convolutional Neural
Networks to reconstruct neutrino interactions in the DeepCore detector. In this
contribution, the recent IceCube result from the atmospheric muon neutrino
disappearance analysis using the CNN-reconstructed neutrino sample is presented
and compared to the existing worldwide measurements.
