Today, AWS customers use Amazon SageMaker to train and tune millions of machine learning (ML) models with billions of parameters. In this session, learn about advanced SageMaker capabilities that can help you manage large-scale model training and tuning, such as distributed training, automatic model tuning, optimizations for deep learning algorithms, debugging, profiling, and model checkpointing, so that even the largest ML models can be trained in record time for the lowest cost. Then, hear from Aurora, a self-driving vehicle technology company, on how they use SageMaker training capabilities to train large perception models for autonomous driving using massive amounts of images, video, and 3D point cloud data.

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