Learn about designing, training, and evaluating domain-specialized health-care imaging AI models using MONAI. Researchers and data scientists need a common foundation to perform training experiments and compare against the state of the art. MONAI provides domain-specific implementations to help kick-start development and research, including new features like self-supervised learning, Transformer-based Networks for Medical Imaging (UNETR), and DiNTS, a new neural architecture search method. We'll introduce MONAI Core and then dive deep into the more technical features of MONAI, with a hands-on walkthrough of Self-Supervised Learning, AutoML/DiNTS, and researcher best practices. Prerequisite(s): Python Deep Learning Basic familiarity with medical imaging
*Please disregard any reference to "Event Code" for access to training materials. "Event Codes" are only valid during the original live session.
Explore more training options offered by the NVIDIA Deep Learning Institute (DLI). Choose from an extensive catalog of self-paced, online courses or instructor-led virtual workshops to help you develop key skills in AI, HPC, graphics & simulation, and more.