Deep Learning for Autonomous Vehicles: Learning

This lecture covers the learning process in the context of deep learning for autonomous vehicles, focusing on predictive models and recurrent neural networks. Topics include preprocessing data, designing architectures, loss functions, activation functions, optimization strategies, and model ensembles. The lecture also delves into the ImageNet dataset, large-scale visual recognition challenges, and transfer learning with convolutional neural networks.