The DeepCore subdetector of the IceCube Neutrino Observatory provides access to neutrinos with energies above approximately 5 GeV. Data taken between 2012 and 2021 (3387 days) are utilized for an atmospheric ${\nu }_{\mu }$ disappearance analysis that studied 150 257 neutrino-candidate events with reconstructed energies between 5 and 100 GeV. An advanced reconstruction based on a convolutional neural network is applied, providing increased signal efficiency and background suppression, resulting in a measurement with both significantly increased statistics compared to previous DeepCore oscillation results and high neutrino purity. For the normal neutrino mass ordering, the atmospheric neutrino oscillation parameters and their $1\sigma$ errors are measured to be $\mathrm{\Delta }{\mathrm{m}}_{32}^2={2.40}_{-0.04}^{+0.05}\times {10}^{-3}{\mathrm{eV}}^2$ and ${\sin }^2{\theta }_{23}={0.54}_{-0.03}^{+0.04}$. The results are the most precise to date using atmospheric neutrinos, and are compatible with measurements from other neutrino detectors including long-baseline accelerator experiments.